HIV simulation model - Centers for Disease Control and ...



Appendices:Title: Impact of providing pre-exposure prophylaxis for HIV at clinics for sexually transmitted infections in Baltimore City: an agent-based modelAuthors: Parastu Kasaie (PhD)1, Stephen A. Berry (MD)2, Maunank S. Shah (MD, PhD)2, Eli S. Rosenberg (PhD)3, Karen W. Hoover (MD, MPH)4, Thomas L. Gift (PhD)5, Harrell Chesson (PhD)5, Jeff Pennington (BS)1, Danielle German (PhD)1, Colin P. Flynn (ScM)6, Chris Beyrer (MD, PhD)1, and David W. Dowdy (MD, PHD)1 1 Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA 212052 School of Medicine, Johns Hopkins University, Baltimore, MD, USA 212053 Rollins School of Public Health, Emory University, Atlanta, GA, USA 4 Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC5 Division of STD Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC6 Maryland Department of Health and Mental Hygiene, Baltimore, MD, USA, 21201HIV simulation model OverviewOur agent-based simulation model of the HIV epidemic among MSM in Baltimore City is structured as a collection of modules that govern population demographics, sexual partnerships, the epidemiological aspects of disease with regard to HIV natural history, cascade of care and transmission. Each “agent” represents a single MSM in Baltimore City, characterized by age, race, and place of residence, and the model is evaluated in a series of one-week time steps. The HIV natural history module characterizes the progression of HIV among infected individuals according to disease stage (acute, chronic, and late). Each stage is associated with a different per-act risk of HIV transmission, and progression from chronic to late disease can be prevented (and/or reversed) by provision of ART. The HIV cascade of care estimates probabilities of HIV testing, linkage to care, disengagement/re-engagement, and ART provision/viral suppression at each time step. The sexual network and transmission module create and modify the population’s sexual networks (as a series of stable and casual partnerships) at each step, modeling HIV transmission as a per-act probability among serodiscordant partnerships according to frequency and safety of sex act, HIV stage of the infected partner, and ART/PrEP use. Sexual partnerships are modeled as assortative according to age, race, and location of residence. Finally, the population demographic module accounts for aging, death, and birth processes.Population Demographic ModuleThis module characterizes the initial population structure and governs various procedures for aging, death, and birth at end of each simulated year. We model the population of MSM in Baltimore city between the ages of 15 to 75. The population is structured as a collection of population groups corresponding to Baltimore’s Community Statistical Areas (CSA) ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Alliance", "given" : "Baltimore Neighborhood Indicators", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2012" ] ] }, "title" : "Vital Signs 12", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[1]", "plainTextFormattedCitation" : "[1]", "previouslyFormattedCitation" : "[1]" }, "properties" : { }, "schema" : "" }[1]. CSAs are clusters of neighborhoods and are organized according to census tract boundaries, which are consistent statistical boundaries. In some cases, CSA boundaries may cross neighborhood boundaries. There are 55 CSAs in Baltimore City. Neighborhood lines often do not fall along CSA boundaries, but CSAs are representations of the conditions occurring within those particular neighborhoods. Simulated population groups are characterized with regard to their geographical location (CSA of residence) and racial structure (black and non-black). We do not model the spatial distribution of individuals within each CSA; rather geographical assignments are made at the CSA level by assigning the corresponding CSA-center coordinates to each MSM living in that CSA. The initial HIV distribution across CSAs is estimated according to publicly available data from Maryland’s Department of Health and Mental Hygiene (MDHMH) ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Maryland Department of Health and Mental Hygiene", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "MDHMH", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2012" ] ] }, "number-of-pages" : "Maryland Department of Health and Mental Hygiene", "publisher-place" : "Baltimore", "title" : "2012 Baltimore City Annual HIV Epidemiological Profile", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[2]", "plainTextFormattedCitation" : "[2]", "previouslyFormattedCitation" : "[2]" }, "properties" : { }, "schema" : "" }[2].Individuals age with the simulation clock (years) and exit the model according to an age-specific natural mortality rate ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "author" : [ { "dropping-particle" : "", "family" : "World Health Organization", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Global Health Observatory Data Repository", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2013" ] ] }, "title" : "Life tables by country United States of America", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[3]", "plainTextFormattedCitation" : "[3]", "previouslyFormattedCitation" : "[3]" }, "properties" : { }, "schema" : "" }[3] (Table S1), or by reaching the age of 75, or via an additional mortality rate associated with HIV infection. To maintain the initial population decomposition without disturbing the CSA structures, we model a natural birth process at the CSA level for replenishing the population size over time. The birth process is modeled via a non-stationary Poisson process tuned to maintain each CSA’s population at a constant mean over time. Newborns enter the MSM population at age of 15 to 20 years old, and follow the corresponding racial structure of the CSA of residence (Table S2). Using the current estimate of Baltimore City male population (approximately 287,000) who are 15 year or older in age (about 232,000), and estimated percentage of adult MSMs in each racial group (7.5% of non-black males and 5.8% of black males ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Lieb", "given" : "S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Fallon", "given" : "S. J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Friedman", "given" : "S. R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Thompson", "given" : "D. R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gates", "given" : "G. J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Liberti", "given" : "T. M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Malow", "given" : "R. M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Public Health Reports", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "60-72", "title" : "Statewide Estimation of Racial/Ethnic Populations of Men Who Have Sex with Men in the U.S.", "type" : "article-journal", "volume" : "126" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[4]", "plainTextFormattedCitation" : "[4]", "previouslyFormattedCitation" : "[4]" }, "properties" : { }, "schema" : "" }[4]), we estimate the size of Baltimore City’s MSM population at approximately 15,000. Table S1: Age specific mortality ratesAge groupAge-specific mortalityAge groupAge-specific mortality15-200.000845-500.003820-250.001250-550.005825-300.001255-600.008430-350.001460-650.012235-400.001665-700.01840-450.002470-750.027Table S2: List of data on CDA population size, racial decomposition and HIV prevalence. Due to uncertainty of data on CSA age-structure, individuals’ is age is generated according to the overall age-distribution of adult men between ages of 15 to 75 in Baltimore City. CSA IDPopulationPrp BlackHIV prevalenceCSA IDPopulationPrp BlackHIV prevalence13350.8820.0274345282440.0890.0016370122770.7890.0141305292170.9430.020182433820.8690.0401984304360.1150.012434943820.3590.013592313050.580.010606452770.040.00294551323210.8760.013737965420.7850.0197492331640.9030.0079182271420.9510.00717847345040.1160.017574981810.690.00603148354700.3210.036161491930.5310.0361801362010.9560.014649101940.9630.020952372330.1760.0176684112910.2040.0101721381270.2260.0026735112830.8780.00891263394940.1180.0232433132320.9610.014754403710.8860.029016142170.370.030106412110.8950.0365408151510.9670.00726905422780.1220.027809163200.0780.012516434260.380.00395461172050.9490.0244221442170.9030.0600945183240.630.0209389452380.9440.0136391195660.3470.0211398461170.8290.0108575202200.9090.0105845473080.9660.0339919211840.9620.0252312482260.0270.00726864221990.0790.00224012491640.2540.013859233910.9660.0309432502710.9570.0128644241690.9580.0250631514210.7580.0387481253160.5650.0103262521670.7870.0164297261430.5790.014417532080.9240.0246149274260.530.0102959541550.490.00896509551710.6550.00713586Forming CSA-groups: To determine groupings of similar CSAs, we first ranked the CSAs according to the median income level and racial makeup based on available information from Baltimore City census ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Alliance", "given" : "Baltimore Neighborhood Indicators", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2012" ] ] }, "title" : "Vital Signs 12", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[1]", "plainTextFormattedCitation" : "[1]", "previouslyFormattedCitation" : "[1]" }, "properties" : { }, "schema" : "" }[1]. For simplicity, levels of income and proportion of population that is Black/African-American were coded into values from 1 to 5 (representative of various shades in Figure S1), and two values were assigned to each CSA. For example, CSA “Midtown” (T-shaped in the center of the map) was assigned a rank of 3 for median household income, and 2 for the proportion of population that is Black/African-American.? Figure S SEQ Figure \* ARABIC 1: Baltimore city CSA ranking according to median income and racial structure ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Alliance", "given" : "Baltimore Neighborhood Indicators", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2012" ] ] }, "title" : "Vital Signs 12", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[1]", "plainTextFormattedCitation" : "[1]", "previouslyFormattedCitation" : "[1]" }, "properties" : { }, "schema" : "" }[1].We defined a CSA-group to include a number of neighboring CSAs (sharing a border) with at most a one-level difference in their ranked levels of income and racial makeup. To determine the CSA-groups throughout the city, we implemented a random search mechanism using a branch and bound logic. The search was started from a random CSA and branched through all neighboring CSAs to determine how many could belong to the same CSA-group. The search was bounded by those CSAs representing a difference of more than one level in ranked income and racial makeup, but continued for those CSAs that belonged to the same group and branched further to test their other neighbors, until it was bounded in all directions. At the end of each iteration, a list of CSAs grouped by relative similarity across the whole city was generated. This search was repeated many times and the CSA groups that were most likely (i.e., high frequency) to form were identified. Overlapping CSA-groups were further checked for the possibility of combination into a single group. Finally we had 16 CSA-groups across Baltimore City, representing geographically approximate neighborhoods with similar levels of income and racial makeup (Figure S2). Using CSA numbers as identifiers, a complete list of CSA groups is provided in Table S3.Figure S SEQ Figure \* ARABIC 2: Baltimore city CSA ID’s and CSA groups structure. Each CSA group is marked with a closed border in a different color. Some groups overlap such that some CSAs belong to more than one group. Some CSAs may not belong to any groups and are considered by themselves.Table S3: List of CSA group and member CSAsGroup IDCSA members1 11 22 34 38 392 3 6 93 28 42 434 3 6 8 25 27 31 325 42 496 10 24 33 36 41 527 5 16 28 30 43 488 3 6 20 32 409 4 14 19 26 35 54 5510 14 34 3511 1 23 44 45 46 47 50 51 5312 1 51 54 5513 4 14 19 26 35 54 5514 2 13 15 17 21 2915 1 12 13 15 17 21 23 29 44 45 47 50 5116 3 6 10 20 24 33 36 52Sexual Partnership ModuleThis module governs the network of sexual partnerships and runs in discrete time steps, each representing a week. Following previous models of sexual contact networks ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "abstract" : "Epidemics of HIV in men who have sex with men (MSM) continue to expand in most countries. We sought to understand the epidemiological drivers of the global epidemic in MSM and why it continues unabated. We did a comprehensive review of available data for HIV prevalence, incidence, risk factors, and the molecular epidemiology of HIV in MSM from 2007 to 2011, and modelled the dynamics of HIV transmission with an agent-based simulation. Our findings show that the high probability of transmission per act through receptive anal intercourse has a central role in explaining the disproportionate disease burden in MSM. HIV can be transmitted through large MSM networks at great speed. Molecular epidemiological data show substantial clustering of HIV infections in MSM networks, and higher rates of dual-variant and multiple-variant HIV infection in MSM than in heterosexual people in the same populations. Prevention strategies that lower biological transmission and acquisition risks, such as approaches based on antiretrovirals, offer promise for controlling the expanding epidemic in MSM, but their potential effectiveness is limited by structural factors that contribute to low health-seeking behaviours in populations of MSM in many parts of the world.", "author" : [ { "dropping-particle" : "", "family" : "Beyrer", "given" : "Chris", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baral", "given" : "Stefan D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Griensven", "given" : "Frits", "non-dropping-particle" : "van", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Goodreau", "given" : "Steven M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Chariyalertsak", "given" : "Suwat", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wirtz", "given" : "Andrea L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Brookmeyer", "given" : "Ron", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Lancet", "id" : "ITEM-1", "issue" : "9839", "issued" : { "date-parts" : [ [ "2012", "7", "28" ] ] }, "page" : "367-77", "title" : "Global epidemiology of HIV infection in men who have sex with men.", "type" : "article-journal", "volume" : "380" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Marshall", "given" : "Brandon DL", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Paczkowski", "given" : "Magdalena M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Seemann", "given" : "Lars", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Tempalski", "given" : "Barbara", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Pouget", "given" : "Enrique R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Galea", "given" : "Sandro", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Friedman.", "given" : "Samuel R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "PloS one", "id" : "ITEM-2", "issue" : "9", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "e44833", "title" : "A complex systems approach to evaluate HIV prevention in metropolitan areas: preliminary implications for combination intervention strategies", "type" : "article-journal", "volume" : "7" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "DOI" : "10.5210/ojphi.v7i3.6104", "ISSN" : "1947-2579", "abstract" : "Recently, the first comprehensive guidelines were published for pre-exposure prophylaxis (PrEP) for the prevention of HIV infection in populations with substantial risk of infection. Guidelines include a daily regimen of emtricitabine/tenofovir disoproxil fumarate (TDF/FTC) as well as condom usage during sexual activity. The relationship between the TDF/FTC intake regimen and condom usage is not yet fully understood. If men who have sex with men (MSM,) engage in high-risk sexual activities without using condoms when prescribed TDF/FTC they might be at an increased risk for other sexually transmitted diseases (STD). Our study focuses on the possible occurrence of behavioral changes among MSM in the United States over time with regard to condom usage. In particular, we were interested in creating a model of how increased uptake of TDF/FTC might cause a decline in condom usage, causing significant increases in non-HIV STD incidence, using gonococcal infection incidence as a biological endpoint. We used the agent-based modeling software NetLogo, building upon an existing model of HIV infection. We found no significant evidence for increased gonorrhea prevalence due to increased PrEP usage at any level of sample-wide usage, with a range of 0-90% PrEP usage. However, we did find significant evidence for decreased prevalence of HIV, with a maximal effect being reached when 5% to 10% of the MSM population used PrEP. Our findings appear to indicate that attitudes of aversion, within the medical community, toward the promotion of PrEP due to the potential risk of increased STD transmission are unfounded.", "author" : [ { "dropping-particle" : "", "family" : "Escobar", "given" : "Erik", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Durgham", "given" : "Ryan", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Dammann", "given" : "Olaf", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Stopka", "given" : "Thomas", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Online Journal of Public Health Informatics", "id" : "ITEM-3", "issue" : "3", "issued" : { "date-parts" : [ [ "2015" ] ] }, "title" : "Agent-based computational model of the prevalence of gonococcal infections after the implementation of HIV pre-exposure prophylaxis guidelines", "type" : "article", "volume" : "7" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[5\u20137]", "plainTextFormattedCitation" : "[5\u20137]", "previouslyFormattedCitation" : "[5\u20137]" }, "properties" : { }, "schema" : "" }[5–7], we conceptualize the network of sexual partnerships at an individual level (with regard to age, race, geography, sexual positioning, etc.) and calibrate the simulation parameters using local behavioral surveillance data available through the BESURE study, the Baltimore branch of the National HIV Behavioral Surveillance System (NHBS) ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "author" : [ { "dropping-particle" : "", "family" : "German", "given" : "Danielle", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "0" ] ] }, "title" : "BESURE Study: National HIV Behavioral Surveillance Study in Baltimore", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[8]", "plainTextFormattedCitation" : "[8]", "previouslyFormattedCitation" : "[8]" }, "properties" : { }, "schema" : "" }[8]. BESURE is a CDC funded project operated by the Maryland Department of Health and Mental Hygiene and the Johns Hopkins Bloomberg School of Public Health. Starting in 2004, BESURE has conducted four venue based sampling surveys among Baltimore’s MSM (Table S4). We use this data to extract information on several behavioral parameters at the individual level (e.g., preference toward using condoms in each type of partnerships) that will be directly implemented at the agent level, as well as population-level estimates for calibrating the unknown variables (e.g., frequency of the annual sexual partnerships). For those measures available across multiple BESURE waves, we use a pooled estimate of the reported values. Table S4: Survey methods and sample characteristics, BESURE MSM 2004-2010Wave 1Wave 2Wave 3Wave 4DateJune 04-April 05Jul-Oct 2008Aug-Dec 2011Jun-Dec 2014Total MSM645448404455HIV prevalence37.7%37.5%42.6%30.6%Proportion of HIV that was unrecognized58.4%78.4%67.3%33.1%Partnership types and formation We model two types of partnerships representing long-term “stable” and short-term “casual” partnerships. Stable partnerships can last for several years ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "abstract" : "Epidemics of HIV in men who have sex with men (MSM) continue to expand in most countries. We sought to understand the epidemiological drivers of the global epidemic in MSM and why it continues unabated. We did a comprehensive review of available data for HIV prevalence, incidence, risk factors, and the molecular epidemiology of HIV in MSM from 2007 to 2011, and modelled the dynamics of HIV transmission with an agent-based simulation. Our findings show that the high probability of transmission per act through receptive anal intercourse has a central role in explaining the disproportionate disease burden in MSM. HIV can be transmitted through large MSM networks at great speed. Molecular epidemiological data show substantial clustering of HIV infections in MSM networks, and higher rates of dual-variant and multiple-variant HIV infection in MSM than in heterosexual people in the same populations. Prevention strategies that lower biological transmission and acquisition risks, such as approaches based on antiretrovirals, offer promise for controlling the expanding epidemic in MSM, but their potential effectiveness is limited by structural factors that contribute to low health-seeking behaviours in populations of MSM in many parts of the world.", "author" : [ { "dropping-particle" : "", "family" : "Beyrer", "given" : "Chris", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baral", "given" : "Stefan D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Griensven", "given" : "Frits", "non-dropping-particle" : "van", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Goodreau", "given" : "Steven M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Chariyalertsak", "given" : "Suwat", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wirtz", "given" : "Andrea L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Brookmeyer", "given" : "Ron", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Lancet", "id" : "ITEM-1", "issue" : "9839", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "367-77", "title" : "Global epidemiology of HIV infection in men who have sex with men.", "type" : "article-journal", "volume" : "380" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[9]", "plainTextFormattedCitation" : "[9]", "previouslyFormattedCitation" : "[9]" }, "properties" : { }, "schema" : "" }[9], while casual partnerships will only last a single time step (one week) in the model. We assume that individuals can have multiple casual partnerships from one week to the next ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Vieira", "given" : "Israel T.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "de", "family" : "Senna", "given" : "Valter", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Pereira.", "given" : "Hernane B. de B.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Pesquisa Operacional", "id" : "ITEM-1", "issue" : "2", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "373-389", "title" : "A small world model for the spread of HIV infection", "type" : "article-journal", "volume" : "31" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[10]", "plainTextFormattedCitation" : "[10]", "previouslyFormattedCitation" : "[10]" }, "properties" : { }, "schema" : "" }[10], but they can only engage in a maximum of one stable and one casual partnership at any time step. The stable partnership duration is randomly generated at the time of partnership formation. All partnerships are updated at the end of each simulation week, and those partnerships reaching their pre-specified duration will be dissolved. Upon reaching partnership dissolution time, the partnership is broken and individuals are eligible to engage in new stable partnerships with other people in the model. At any time in the model, one of agents die while in a stable partnership, the other agent will be available for forming new partnerships over the next time steps. At the beginning of each following week, individuals’ tendency to engage in a new partnership is evaluated and “eligible” individuals will select the geographical search domain for meeting their future partners based on their location of residence. Once the partnership domains are established for all eligible MSM, individuals will follow a search mechanism based on a combination of race- and age-dependent mixing patterns, as well as sexual role preference, to select their future partner from the pool of eligible people at the selected domain. This process is modeled in 3 steps:Step 1. Evaluating an individual’s probability of engaging in a new partnershipEach individual’s likelihood of engaging in a new partnership is modeled as a function of his age, the level of sexual activity, and current partnership status. In accordance with the heterogeneous frequency of reported partnerships by age, we define a partnership coefficient for modeling the likelihood of engaging in new partnerships as a function of individual’s age (cPart|Age) (assumed to be a fixed level for each age group). Furthermore, we model the heterogeneous level of sexual activity among MSM by assuming three sexual activity classes, each corresponding to a lifetime level of engagement in casual partnerships. An individual’s sexual activity class (cSA) is determined at the time of birth (entry to population) and remains fixed throughout his life (though within each sexual activity class, the actual level of partnership formation changes with age – for example, partnership formation declines with older age in all three classes). This attribute represents a combination of factors determining an individual’s tendency for engaging in casual partnerships, reflecting the diversity of sexual activity seen in real populations. For simplicity, we assume equal probability of membership to each sexual activity class at the population level, and we calibrate the corresponding level of sexual activities in each class to provide the reported frequency of annual partnerships from data.Finally, we model each agent’s tendency for engaging in casual and stable partnerships at any point of time via two additional parameters (pCsl and pStb) at the agent-level, and also define the conditional likelihood of engaging in new casual partnerships concurrent to an existing stable partnership via a separate parameter (pCsl|Stb).With these definitions, an individual’s likelihood of engaging in a new stable (Pnew_stb) or casual (Pnew_csl) partnership at each timestep can be estimated as follow:Pnew_stb = pStb × cPart|AgePnew_csl = pCsl × p Csl|Stb* × cPart|Age × cSApCsl|Stb*=pCsl|Stb number of stable partnerships > 0 1 o.w.At each time step, an individual’s likelihood for engaging in a new partnership is evaluated and eligible individuals are added to the pool of available people at their CSA of residence to find their potential partners in the next steps. Step 2. Choosing the partnership domainThe partnership domain is determined according to a discrete mixing structure at the CSA level (Figure S3). In order to model the spatial mixing patterns across the population and among various subgroups, we first define sets of “neighboring” CSA groups with regard to geographical proximity and similar socioeconomic status (income levels) and racial structure ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Alliance", "given" : "Baltimore Neighborhood Indicators", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2012" ] ] }, "title" : "Vital Signs 12", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[1]", "plainTextFormattedCitation" : "[1]", "previouslyFormattedCitation" : "[1]" }, "properties" : { }, "schema" : "" }[1]. Upon seeking a new partnership, an individual’s search scope (for choosing the new partner) is determined according to a discrete geographical mixing probability (pGM ) for selecting one’s own CSA (p0), a random neighboring CSA in the same CSA group (p1) or non-neighbor CSA (p2). The geographical mixing probability (pGM=(p0, p1, p2)) represents a measure of geographical/socioeconomic clustering in the network of partnerships, where pGM=(1,0,0) translates into an isolated mixing pattern for partnership only with individuals in one’s CSA of residence, and pGM=(0.33,0.33,0.33) translates into a homogeneous mixing structure across the entire population. In our initial analysis, we calibrate the geographical mixing likelihoods at pGM = (0.5, 0.3, 0.2) according to available estimates from ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Egan", "given" : "James E.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Frye", "given" : "Victoria", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kurtz", "given" : "Steven P.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Latkin", "given" : "Carl", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Chen", "given" : "Minxing", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Tobin", "given" : "Karin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Yang", "given" : "Cui", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Koblin", "given" : "Beryl A.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "AIDS and Behavior", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "35-50", "title" : "Migration, neighborhoods, and networks: approaches to understanding how urban environmental conditions affect syndemic adverse health outcomes among gay, bisexual and other men who have sex with men", "type" : "article-journal", "volume" : "15" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[11]", "plainTextFormattedCitation" : "[11]", "previouslyFormattedCitation" : "[11]" }, "properties" : { }, "schema" : "" }[11].Figure S3: Partnership search domains. Individuals can choose their future partner from their own CSA or a random CSA within or outside their neighbor group.Step 3. Modeling the search mechanism within the partnership domainOnce the partnership domain is established, individuals follow a search mechanism for finding their new partners from the pool of eligible members in the selected domain. The probability of partnership between two people is evaluated according to an age- and race-mixing structure, as well as sexual role preference. Assuming independent patterns of age- and race-specific mixing, the age-race mixing probability is computed as the product of age-mixing and race-mixing probabilities for each pair of potential partners. A random search mechanism is implemented to evaluate the probability of partnership with each potential partner in the selected domain until a successful match is found or the entire domain is searched. Potential partners are also checked for their compatibility with regard to sexual role and incompatible pairs (e.g., receptive-receptive or insertive-insertive) are dismissed. Upon a successful match, a new partnership is formed for both parties, who are then excluded from the pool of eligible partners for other individuals.Age-Specific Mixing Age-specific mixing is modeled based on absolute difference in the square root (ADSR) of men’s ages ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "abstract" : "Epidemics of HIV in men who have sex with men (MSM) continue to expand in most countries. We sought to understand the epidemiological drivers of the global epidemic in MSM and why it continues unabated. We did a comprehensive review of available data for HIV prevalence, incidence, risk factors, and the molecular epidemiology of HIV in MSM from 2007 to 2011, and modelled the dynamics of HIV transmission with an agent-based simulation. Our findings show that the high probability of transmission per act through receptive anal intercourse has a central role in explaining the disproportionate disease burden in MSM. HIV can be transmitted through large MSM networks at great speed. Molecular epidemiological data show substantial clustering of HIV infections in MSM networks, and higher rates of dual-variant and multiple-variant HIV infection in MSM than in heterosexual people in the same populations. Prevention strategies that lower biological transmission and acquisition risks, such as approaches based on antiretrovirals, offer promise for controlling the expanding epidemic in MSM, but their potential effectiveness is limited by structural factors that contribute to low health-seeking behaviours in populations of MSM in many parts of the world.", "author" : [ { "dropping-particle" : "", "family" : "Beyrer", "given" : "Chris", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baral", "given" : "Stefan D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Griensven", "given" : "Frits", "non-dropping-particle" : "van", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Goodreau", "given" : "Steven M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Chariyalertsak", "given" : "Suwat", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wirtz", "given" : "Andrea L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Brookmeyer", "given" : "Ron", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Lancet", "id" : "ITEM-1", "issue" : "9839", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "367-77", "title" : "Global epidemiology of HIV infection in men who have sex with men.", "type" : "article-journal", "volume" : "380" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[9]", "plainTextFormattedCitation" : "[9]", "previouslyFormattedCitation" : "[9]" }, "properties" : { }, "schema" : "" }[9]. The ADSR provides a closer fit to the observed age-mixing matrix than does age directly. This statistic also has the desirable property that the same absolute difference in age becomes less important over time. Using data on participant’s age and their last male partner’s age from BESURE, we estimate the reported ADSR level for main/casual partnerships (ADSRpartnership) as shown in Table S5. The probability of age-mixing between person p and q for each partnership type (pAgeMixing) is then computed as a function of partners’ age and the target ADSR level for each type of partnerships. Figure S4 compares the simulated distribution of ADSR values among casual and stable partnerships in the baseline simulation model.pAgeMixing = Min(ADSRp,q , 2 × ADSRpartnership – ADSRp,q)/ ADSRpartnershipwhere ADSRp,q= page –qage ADSRpartnership = (ADSRStb ,ADSRCsl)Table S5: Estimates of reported ADSR for Stable/Casual partnerships in BESURE. Estimates are made based on the participant’s age and their last male partner’s age.BESURE Waves:ADSRStb(Number of reported partnerships)ADSRCsl (Number of reported partnerships)Wave 2 0.62 (66)0.72 (75)Wave 3 0.68 (71)0.73 (87)Wave 4 0.51 (62)0.76 (77)Average estimate 0.60.74Figure S4: Distribution of ADSR in simulated casual (Panel A) and stable (Panel B) partnerships at the baseline model. Race-MixingWe model the probability of partnership between MSM of the same sex by estimating the reported ratio of same-sex partnerships for Black MSM at 90% and for Non-black MSM at 75% through BESURE data.Sexual Role PreferenceEach MSM is assigned an individual sexual role preference (insertive only, receptive only, versatile) at the time of birth (entry to population). The sexual role preferences prohibit the partnerships between two men who are insertive only or those who are receptive only (allowing for 5 partnership configuration). The type of sexual act in partnerships between two versatile men is determined via uniform probability distribution between 0 and 1 (e.g., 50% chance of insertive/receptive act for each men), and will be updated at each time step for their active partnerships. Using data from BESURE, we estimate the proportions of population that fall within each category at 42% insertive-only, 26% receptive-only, and 32% versatile.Potential limitations and implications for study of PrEP impactAs with any modeling study, our analysis is limited by necessary simplifying assumptions made in development and calibration of our simulation model. Our simplified assumption for limiting the maximum number of stable partnerships to 1 partner at each time was supported by available data from Baltimore City. Using available data from the BESURE study (Baltimore branch of the National HIV surveillance study), we estimated the annual frequency of stable partnerships reported by MSM. This results suggested that the majority of MSM (>90%) have 0 or 1 stable partner in any given year. As such, we limited the number of stable partnerships to a maximum of 1 partner at any time in the model. To the degree that MSM engage in more than 1 stable partnership over time, our results may underestimate the level of concurrency in networks of stable partnerships.Moreover, in absence of descriptive data to differentiate various types of ‘non-stable’ partnerships (e.g., one-time partnerships, long-term friendships, mid-term relationships), we defined ‘casual’ partnerships as short-term partnerships with a duration of one week and assumed that individuals can engage in up to 1 casual partnership in any given time. While this approach does not allow for capturing concurrency in more than two partnerships (a stable and casual partnership) at any given week, the short duration of casual partnerships in our model allows for high partner turnover over time. Thus, while we again do not model time steps in which multiple concurrent partnerships are formed, the model does allow for “effective” concurrency (e.g., an individual is infected with HIV and then develops new partnerships at nearly every time step before being diagnosed and started on ART), which we believe is likely to represent the same explosive sort of transmission that can occur in the context of group sex or sex work.Based on these assumptions, our model is unable to capture transmission pathways across concurrent casual partnerships with great precision, however, such transmissions should arguably have little effect on the *relative* impact of PrEP – unless PrEP were assumed to be taken differentially in the context of high-concurrency settings (an assumption which may be true, but for which we have no existing data). Moreover, we have calibrated the overall frequency and types of reported partnerships (i.e., proportion of those reporting a stable-only, casual-only or stable-casual partnerships) in any given year – such that the total number of partnerships should reflect the available data, even if the model does not allow those partnerships to be highly concurrent.HIV Epidemiological ModuleThis module governs various aspects of HIV natural history and cascade of care, and it is updated at the end of each time step (week).HIV Natural HistoryUpon a successful HIV transmission event, individuals experience a gradual increase in viral load (VL) and move through various stages of disease (Figure 1, main manuscript). We consider three disease stages in absence of ART, including acute infection (CD4 count > 500 cells/ ?L), chronic infection (CD4 count between 200-500 cells/ ?L) and late infection (CD4 count <200 cells/ ?L). Each disease stage is characterized with regard to duration of disease (as a crude measure of CD4 decline over time), mean VL level (determining the level of infectiousness) as well as the HIV mortality rate. In this model, we do not model the dynamics in the number of CD4 counts directly, but rather use the defined disease stages as surrogate marker of VL and mortality level for all HIV+ individuals. HIV Cascade of CareThe continuum of care for infected individuals is modeled in five levels corresponding to those 1) unaware of their HIV infection, 2) diagnosed with HIV but not linked to care, 3) linked to care but not engaged in care, 4) engaged in care and on ART, and 5) engaged in care but not taking ART (Figure 1, main manuscript). HIV-positive individuals are subject to a probability of screening for HIV at the beginning of each week. Upon diagnosis with HIV, individuals experience a fixed likelihood of linking to care over the following weeks. Once linked to care, individuals are assumed to engage in HIV care and start ART immediately. HIV-positive individuals taking ART will experience partial VL suppression in the first few months after ART initiation, and will achieve full VL suppression afterward. Taking ART will further lower the disease mortality rate at each disease stage to a certain degree ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "The INSIGHT START Study Group", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "N Engl J Med", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2015" ] ] }, "page" : "795-807", "title" : "Initiation of antiretroviral therapy in early asymptomatic HIV infection", "type" : "article-journal", "volume" : "373" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Kitahata", "given" : "Mari M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gange", "given" : "Stephen J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abraham", "given" : "Alison G.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Merriman", "given" : "Barry", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Saag", "given" : "Michael S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Justice", "given" : "Amy C.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Al", "given" : "Robert S. Hogg et", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "New England Journal of Medicine", "id" : "ITEM-2", "issue" : "18", "issued" : { "date-parts" : [ [ "2009" ] ] }, "page" : "1815-1826", "title" : "Effect of early versus deferred antiretroviral therapy for HIV on survival", "type" : "article-journal", "volume" : "360" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Palella Jr", "given" : "Frank J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Delaney", "given" : "Kathleen M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Moorman", "given" : "Anne C.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Loveless", "given" : "Mark O.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Fuhrer", "given" : "Jack", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Satten", "given" : "Glen A.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Aschman", "given" : "Diane J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Holmberg", "given" : "Scott D.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "New England Journal of Medicine", "id" : "ITEM-3", "issue" : "13", "issued" : { "date-parts" : [ [ "1998" ] ] }, "page" : "853-860", "title" : "Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection", "type" : "article-journal", "volume" : "338" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[12\u201314]", "plainTextFormattedCitation" : "[12\u201314]", "previouslyFormattedCitation" : "[12\u201314]" }, "properties" : { }, "schema" : "" }[12–14]. We assume that individuals starting ART through late infection (with CD4 count < 200 cells/ ?L) will continue to experience the late-stage mortality level (adjusted with ART reduction factor) for one year before reverting back to the chronic stage (and experiencing the chronic stage mortality level adjusted with ART reduction factor).Those on ART can become non-adherent to treatment over time and/or become disengaged in care. These individuals are subject to a weekly probability of reengagement in care and reinitiating ART in the future, but cannot reinitiate ART for 6 months after discontinuation ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Rana", "given" : "Aadia I.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Liu", "given" : "Tao", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gillani", "given" : "Fizza S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Reece", "given" : "Rebecca", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kojic", "given" : "Erna M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Zlotnick", "given" : "Caron", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilson", "given" : "Ira B.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "AIDS care", "id" : "ITEM-1", "issue" : "6", "issued" : { "date-parts" : [ [ "2015" ] ] }, "page" : "697-687", "title" : "Multiple gaps in care common among newly diagnosed HIV patients", "type" : "article-journal", "volume" : "27" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[15]", "plainTextFormattedCitation" : "[15]", "previouslyFormattedCitation" : "[15]" }, "properties" : { }, "schema" : "" }[15]. Once off ART, individuals are assumed to lose viral suppression immediately and to experience a rapid decline in their CD4 counts. For simplicity, we assume that the effect of ART on CD4 count levels is maintained for one year following discontinuation (unless the agent was not previously on ART for a year, in which case the duration of ART is used) – and we also add this amount of time to the individual’s “clock” of progression for HIV disease. Thus, for example, an individual starting ART in the chronic stage and taking ARE for 6 months before discontinuation will go back to the chronic stage, but the time until progression to late stage is prolonged by 6 additional months. We further assume that those starting ART in acute stage will return to chronic stage if they discontinue treatment, and those beginning ART through late stage can revert to chronic or late stage depending on the duration of treatment. HIV TransmissionHIV transmission is evaluated for all active partnerships between HIV-positive individuals and susceptible partners at the end of each week. The probability of transmission is modeled as a function of an infected partner’s infectiousness for transmitting HIV, the immunity of the negative partner toward transmission with HIV (through PrEP), potential protection through condom use, and an additional coefficient tuning the overall probability of transmission. HIV infectiousness is modeled as a function of an individual’s VL corresponding to his disease stage and care status, as noted in Table 1 of the main manuscript. An individual’s immunity to infection is modeled as a function of PrEP use and adherence, ranging from 0 (in absence of PrEP) to 1 (full adherence to PrEP). The probabilities of condom use in casual and stable partnerships are estimated based on reported levels through BESURE (Table S6). Finally, the transmission coefficient captures the baseline probability of HIV transmission per contact, and is calibrated to reflect disease prevalence at equilibrium. Table S6: Reported frequency of condom use in stable and casual partnerships from BESURE.NeverPart-timeThe whole timeStable partnership0.450.550Casual partnership0.470.120.4With these definitions, the weekly likelihood of HIV transmission through an active sexual contact is estimated as follow:PtransX,Y,Q= C × XInf× Ysus × (1- pCondumUse(Q)× cCondomEffectiveness) × YsexualPositionCoefwherePtrans(X,Y,Q): Per week probability of transmission from person X (infected) to Y (susceptible) in a partnership type Q (stable, casual)C:Simulation coefficient YInf : Person Y’s infectiousness XSus : Person X’s susceptibility toward infectionpCondomUse(Q): Probability of using condom in partnership type QcCondomEffectiveness: condom effectiveness in reducing the risk of transmission YsexualPositionCoef: Person Y’s increased probability of transmission based on sexual positioningPrEP ScenariosWe incorporated a simulated STI clinic into the model, as the point of PrEP delivery to HIV-negative MSM. Our research aim is to assess the population-level impact of PrEP delivery in STI clinics on HIV incidence. Our primary outcome is the percent reduction in HIV incidence among MSM after implementation of PrEP in the modeled STI clinic (“Strategy 1”), measured relative to a baseline with no PrEP and also against a PrEP delivery strategy implemented in the community at large (“Strategy 2”)- See main manuscript for definition of each strategy.Eligibility: According to CDC guidelines, we assume that all HIV-negative MSM reporting a casual partnership in the last six months or those in a stable sexual partnership with an HIV positive person are eligible to receive PrEP. Those on PrEP are assumed to return every 3 months for eligibility reassessment with those who no longer meet the eligibility criteria discontinuing PrEP, but can initiate it at a later time in the model (upon meeting eligibility criteria). Adherence: We model adherence to PrEP as the percentage of days on which the individual is protected against?infection, ranging from 0% to 100%. While adherence, as defined here, is not empirically measurable, it may be estimated, for example, using serum drug levels. In determining the impact of PrEP on HIV incidence, the ultimate mechanism of interest is not the number of pills taken, but rather the proportion of potential transmission events (primarily condomless sex) that occur during a time when the HIV-negative partner is immunologically protected by PrEP. This is, of course, an immeasurable quantity – but we wish to draw attention to the fact that it is, in fact, the parameter of greatest interest. It is not the percentage of individuals who have adequate levels of adherence per se, but rather the proportion of potential transmission events that occur while individuals are protected. For example, if taking one pill of PrEP would provide protection for 2 days, taking one pill every other day is much better than taking all the pills once a week and not taking any pills during the following week. In the extreme scenario (e.g., intramuscular depot formulation of PrEP), high levels of protection could be achieved with very low daily “adherence”. Finally, since we do not explicitly model discontinuation within each 3-month period, adherence as defined for this exercise will be lower than what might be measured among cohorts of MSM who have not discontinued PrEP. Simulation Calibration Upon collection of all individual-level data and incorporation into the model (fixed parameters), we calibrated the model as a whole against population-level targets (above) to ensure that the model provides realistic outputs. This was done via a random search mechanism to find the best combination of parameter values that minimizes the observed difference between simulated outputs and the calibration targets.Simulation and analytic approach In the absence of PrEP, we first develop a large series of independent simulations. Each simulation is first carried out over a “burn-in” phase until equilibrium is reached among a population equal in size and HIV prevalence to Baltimore’s estimated 3,300 MSM living with HIV in 2014 ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Maryland Department of Health and Mental Hygiene", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "MDHMH", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2012" ] ] }, "number-of-pages" : "Maryland Department of Health and Mental Hygiene", "publisher-place" : "Baltimore", "title" : "2012 Baltimore City Annual HIV Epidemiological Profile", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[2]", "plainTextFormattedCitation" : "[2]", "previouslyFormattedCitation" : "[2]" }, "properties" : { }, "schema" : "" }[2]. After this baseline experience without PrEP is achieved, we carry each simulation forward for an additional 20 years under each PrEP strategy described above. We compare the community-based strategy to the STI clinic-based strategy in two ways: (a) assuming the same number of MSM are assessed for PrEP eligibility every year under each strategy, and (b) assuming the same number of MSM start PrEP every year under each strategy (i.e., more assessments in the community-based strategy since fewer people are eligible to receive PrEP than in the STI clinic-based strategy). The analysis is repeated for different levels of PrEP adherence (range [0%-100%]) and uptake (range [0%-100%]) in each PrEP strategy. For every adherence/uptake combination, we perform roughly 500 independent simulations. The number of simulation replications was selected to provide a precision of at worst +/-5% around each main simulation outcome. The primary outcomes are the projected reduction in HIV incidence and prevalence, relative to the baseline levels in the absence of PrEP. The relative impact of STI clinic-based delivery was calculated as the mean reduction in incidence over simulations with?STI clinic-based delivery, divided by the mean reduction in incidence over those same simulations, assuming community-based PrEP delivery. Ninety-five percent uncertainty ranges were calculated as the 2.5th and 97.5th percentiles of 2000 bootstrap samples, each of size 200, (a sample size determined a priori to provide sufficient stability in estimates) sampled with replacement from the initial set of simulations performed. Finally, we performed one-way sensitivity analysis of simulation outputs to variation of all model parameters to +/- 20% of their original value.Calibrating resultsBESURE surveys (2004 – 2014) provide the main source of local information available on the network of MSM sexual partnerships in Baltimore. The data include aggregate information for the reported number of sexual partners (by age group) and type of those partnerships in the last 12 months. Assuming a fixed mixing structure over time, we use this information to calibrate the individual-level likelihood of engaging in a stable or casual partnership at each simulated time step (week). We use the coefficients of sexual activity to calibrate the right and left tail of the partnership frequency distribution (for those MSM reporting 0 or more than 5 partners in a given year). In the absence of data on duration of undiagnosed HIV disease, the official HIV surveillance reports – to which our model is calibrated – do not provide estimates of HIV incidence. Instead, they report numbers of new HIV diagnoses and estimated levels of HIV prevalence in key populations. As such, we have used reported estimates of HIV prevalence, annual mortality, and the HIV care continuum (proportion of infected population aware of their HIV status, on ART and virally suppressed), as the main calibration targets for our simulation model (See Figure S5), rather than incidence per se (as there is no official estimate of HIV incidence in Baltimore City). 40468553675913HIV prevalence00HIV prevalenceFigure S5: Model calibration to data for (A) frequency of all partnerships, (B) types of partnerships, (C) cascade of HIV Care, and (D) HIV prevalence. Shown are the mean values of 100 simulations (in green) compared against empirical data (in red). The error bars around simulated values represent the 95% uncertainty range of observations around each simulated measure. The error bars around the data in Panels A&B represent the range of annual observations through the BESURE surveys from 2004 to 2014. Data used for calibration in Panels C&D are only available as point estimates in year 2012.As a confirmatory analysis, we also cross-checked our estimated proportion of incidence to prevalence of HIV among MSM in the model of Baltimore City against recently published estimates of HIV incidence among MSM in the US ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Sullivan", "given" : "Patrick S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Peterson", "given" : "John", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rosenberg", "given" : "Eli S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kelley", "given" : "Colleen F.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Cooper", "given" : "Hannah", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vaughan", "given" : "Adam", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Salazar", "given" : "Laura F.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Frew", "given" : "Paula", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wingood", "given" : "Gina", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Diclemente", "given" : "Ralph", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rio", "given" : "Carlos", "non-dropping-particle" : "del", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Mulligan", "given" : "Mark", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Sanchez", "given" : "Travis H.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "del", "family" : "Rio", "given" : "Carlos", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Mulligan", "given" : "Mark", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Sanchez", "given" : "Travis H.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "PloS one", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "e90514", "title" : "Understanding racial HIV/STI disparities in black and white men who have sex with men: a multilevel approach.", "type" : "article-journal", "volume" : "9" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[16]", "plainTextFormattedCitation" : "[16]", "previouslyFormattedCitation" : "[16]" }, "properties" : { }, "schema" : "" }[16]. Singh et al. (2018) estimate an incidence to prevalence ratio of 4.8% to 6.7% among African American MSM (4.1-5.4% overall). Our corresponding estimate is 6.1%. Considering that an estimated 76% of MSM in Baltimore City are African American, we feel that our incidence:prevalence ratio is reasonable, and as such (since our estimate of HIV prevalence is calibrated to official estimates) expect that our projected incidence is also in line with the underlying HIV incidence in Baltimore. Calibrating racial disparity in HIV infectionIn order to capture the reported levels of disparity in number of MSM living with HIV in Baltimore City, we initiated the simulation population according to the reported levels of HIV infection in each age- and race-group, and incorporated information on age- and race-assortative mixing pattern among black and white MSM that may partially explain the higher concentration of HIV infection in the network Black MSM in Baltimore City. Furthermore, we modeled the differential levels of accessing care among Black and White MSM, and calibrated it to reported disparities in care cascade ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "abstract" : "Epidemics of HIV in men who have sex with men (MSM) continue to expand in most countries. We sought to understand the epidemiological drivers of the global epidemic in MSM and why it continues unabated. We did a comprehensive review of available data for HIV prevalence, incidence, risk factors, and the molecular epidemiology of HIV in MSM from 2007 to 2011, and modelled the dynamics of HIV transmission with an agent-based simulation. Our findings show that the high probability of transmission per act through receptive anal intercourse has a central role in explaining the disproportionate disease burden in MSM. HIV can be transmitted through large MSM networks at great speed. 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With these assumptions, the estimated proportion of HIV prevalence attributable to Black MSM was 76% which agreed with reported data from Baltimore City (Figure S6). Figure S6: Simulated distribution of HIV continuum of HIV care and HIV prevalence by race. Shown are the mean values of 200 simulations comparing the HIV continuum of care (Panel A) and proportion of HIV prevalence (Panel B) by racial composition (black MSM are shown in dark and white MSM are shown in light bars). The error bars represent the 90% uncertainty range of observations around each simulated measure. List of model parameters Table S7 provides a list of model parameters at baseline.Table S7: List of model parametersParametersValueReference Looking for new partnershipsWeekly probability of looking for a new casual partnership0.09CalibratedWeekly probability of looking for a new stable partnership0.02CalibratedReduction in probability of casual partnership frequency for those with a stable partner0.35CalibratedCoefficient of partnerships with age ([18-24], [25-34], [35-44], [45-60], [60+] years)[1.0, 1,0, 0.7, 0.4, 0.4]CalibratedCoefficient of sexual activity (low, med, high activity classes)[0.2, 1.3, 3.0]CalibratedMixing patternsCoefficient of geographical mixing (within CSA, within neighboring CSAs, outside) [0.5, .03, 0.2]AssumptionCoefficient of mixing based on race (White-White, Black-Black, White-Black)[0.081, 0.99, 0.07]CalibratedCoefficient of age difference (for modeling assortative mixing patterns)4CalibratedHIV transmissionPer week probability of HIV transmission within ongoing partnerships (adjusted by other cofactors)0.0122CalibratedAverage viral load (log10 copies/mL)(early, chronic, late, partial suppression, full suppression)[1.0, 6.5, 4.5, 5, 3.5, 1.5]ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "abstract" : "Epidemics of HIV in men who have sex with men (MSM) continue to expand in most countries. 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However, the potential epidemiologic impact of treatment in the context of a broader strategy for HIV/AIDS control has not yet been examined. In this paper, we quantify the opportunities and potential risks of large-scale treatment roll-out. METHODS AND FINDINGS: We used an epidemiologic model of HIV/AIDS, calibrated to sub-Saharan Africa, to investigate a range of possible positive and negative health outcomes under alternative scenarios that reflect varying implementation of prevention and treatment. In baseline projections, reflecting \"business as usual,\" the numbers of new infections and AIDS deaths are expected to continue rising. In two scenarios representing treatment-centered strategies, with different assumptions about the impact of treatment on transmissibility and behavior, the change in the total number of new infections through 2020 ranges from a 10% increase to a 6% reduction, while the number of AIDS deaths through 2020 declines by 9% to 13%. A prevention-centered strategy provides greater reductions in incidence (36%) and mortality reductions similar to those of the treatment-centered scenarios by 2020, but more modest mortality benefits over the next 5 to 10 years. If treatment enhances prevention in a combined response, the expected benefits are substantial-29 million averted infections (55%) and 10 million averted deaths (27%) through the year 2020. However, if a narrow focus on treatment scale-up leads to reduced effectiveness of prevention efforts, the benefits of a combined response are considerably smaller-9 million averted infections (17%) and 6 million averted deaths (16%). Combining treatment with effective prevention efforts could reduce the resource needs for treatment dramatically in the long term. In the various scenarios the numbers of people being treated in 2020 ranges from 9.2 million in a treatment-only scenario with mixed effects, to 4.2 million in a combined response scenario with positive treatment-prevention synergies. CONCLUSIONS: These analyses demonstrate the importance of integrating expanded care activities with prevention activities if there are to be long-term reductions in the number of new HIV infections and significant declines in AIDS mortality. 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afterward[0.24, 0.5, 0.9]ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2015" ] ] }, "title" : "Marylan Department of Health and Mental Hygeine", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[26]", "plainTextFormattedCitation" : "[26]", "previouslyFormattedCitation" : "[26]" }, "properties" : { }, "schema" : "" }[26]Coefficient of losing adherence to ART0.7CalibratedGap in care upon discontinuing ART (weeks)26PrEPAnnual number STI clinic visits among MSM966ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Prevention", "given" : "Centers for Disease Control", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2014" ] ] }, "title" : "Preexposure Prophylaxis for the Prevention of HIV Infection in the United States \u2013 2014 Clinical Practice Guideline", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[27]", "plainTextFormattedCitation" : "[27]", "previouslyFormattedCitation" : "[27]" }, "properties" : { }, "schema" : "" }[27]PrEP reassessment period3 monthsADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Singh", "given" : "Sonia", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Song", "given" : "Ruiguang", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Johnson", "given" : "Anna Satcher", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "McCray", "given" : "Eugene", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hall", "given" : "H. Irene", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Annals of internal medicine", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2018" ] ] }, "title" : "HIV Incidence, HIV Prevalence, and Undiagnosed HIV Infections in Men Who Have Sex With Men, United States", "type" : "article-journal" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "[28]", "plainTextFormattedCitation" : "[28]", "previouslyFormattedCitation" : "[28]" }, "properties" : { }, "schema" : "" }[28]PrEP Adherence 60% [range 0 to 100%]PrEP uptake 60% [range 0 to 100%]Results Compared against a simulated community-based screening approach, targeting PrEP to MSM attending STI clinics can increase the population level impact of PrEP through 3 mechanisms: MSM recruited from STI clinics for PrEP evaluation (1) are more likely than those who are randomly selected from community to be eligible for PrEP (See Figure 2 in the main text), (2) are more likely to stay eligible for continuing PrEP over time – leading to higher population-level coverage of PrEP– and (3) are more likely to engage in HIV-related high-risk behaviors that lead to future HIV infection. Figure S7 compares the distributions of individuals’ time on PrEP in two scenarios for community-based screening (Panel A) versus STI targeted PrEP (Panel B), compared at equal levels of screening. Time on PrEP is computed as time from PrEP initiation to discontinuation for each person in the model, estimated from 200 independent simulations (assuming 60% uptake, 60% adherence, and 100% retention). Those taking PrEP will remain on PrEP until returning for reassessment (every 3 months) or death. Upon reassessment, individuals who don’t meet the eligibility criteria for PrEP will stop taking medication, but they can restart PrEP at a future time in the model. Given the younger age and higher level of sexually activity among MSM attending STI clinics, a larger proportion of these individuals meet the eligibility criteria for PrEP (Figure 2 in the main text) and also remain eligible for continuing PrEP over time (2.04 [95% UR: 0.26 – 8.07] years on PrEP) compared to individuals who are recruited randomly from the community (1.53 [95% UR: 0.26 – 7.0] years on PrEP). Figure S7: Distribution of individuals’ time on PrEP in community-based screening (A) and STD clinic-targeted (B) scenarios. This leads to higher coverage of PrEP at the population-level over time, when targeted to STI clinic attendees. Figure S8 compares the population level coverage of PrEP among HIV-negative MSM over time. Assuming an uptake and adherence of 60%, the STI-clinic campaign reaches a 10.6% [9.9% - 11.4%] coverage among HIV-negative MSM over 20 years of implementation (yellow line), compared to 5.9% [5.3% - 6.5%] and 8.1% [7.4% - 8.7%] coverage through a community-based campaign at equal levels of screening (green line) and equal levels of delivery (blue line). Similar relationship is observed at various levels of PrEP uptake (Table S8).Figure S8: Impact of STI clinic-based versus community-based PrEP delivery. Shown on the y-axis is the projected coverage of PrEP among HIV-negative MSM at each point of time through alternative PrEP campaigns, assuming 60% adherence and uptake of PrEP across all scenarios.Table S8: Coverage of PrEP among HIV-negative population at various levels of PrEP uptake. Assuming 60% adherence to PrEP, the values compare 20-year achievable coverage of PrEP across alternative PrEP scenarios.Uptake20-year PrEP coverage (%)STI clinic targetedCommunity-based screening: equal evaluationsCommunity-based screening: equal delivery0.24.42.33.20.47.84.25.80.610.65.98.10.8137.410114.98.711.7Sensitivity analysisOne-way sensitivity analysis of main outputs to variation in all model parametersParameter settingOne-way sensitivity analysis of simulation results was performed with regard to all model parameters. For this purpose, we changed each parameter to +/- 20% of its original value, one at a time (keeping all others fixed at the original value), and evaluated the main simulation outputs after such variation (see below). We initially ran the calibrated simulation model (for 100 years) to reach a steady state at baseline, and used this model as a shared platform to run (and synchronize) all sensitivity analyses. In each sensitivity analysis experiment, we changed a single parameter, ran the model for another 25 years to allow for new parameter setting to settle, and then collected simulation outputs. For computational efficiency, all sensitivity analysis configurations were synchronized to run on a single instance of the simulation model in each round of analysis, and the analysis was repeated 200 times (generating independent simulation models) to provide an at-worst precision of 5% around the main simulation output (HIV prevalence) at baseline. The primary output of interest for the sensitivity analysis was the impact of PrEP on HIV incidence achievable with the STI clinic campaign relative to random comparators, assuming 966 annual visits, uptake and adherence of 60%. Impact of PrEP was defined as percent improvement in underlying incidence after 10 yeas since start of the PrEP campaign. Sensitivity Analysis ResultsUsing a threshold of 20% to detect significant changes in the outputs from their baseline levels, the absolute impact of PrEP in each scenario was sensitive to variation in value of parameters pertaining to HIV transmission (Figure S9). These included the probability of starting new casual partnerships (pStartCasualPart), coefficient of sexual activity in high-activity class (cSaLevelHigh), level of HIV viral load in chronic and late HIV states (cHivVL2 & cHivVL3), and effectiveness of condoms in protecting against HIV transmission (cCondomEff_hiv). Our results suggest that under fixed level of screening, the relative impact of PrEP in two simulation scenarios was sensitive to variation in transmission related parameters in the model and had a negative relationship with the force of infection (Panel B). i.e., At equal levels of screening, the relative impact of PrEP in the STI clinic campaign compared to a random screening campaign was increased as the force of infection was decreased (through increased level of condom use or reduction in per act risk of transmission). A reduction in force of infection among general population resulted in decreased efficiency of random screening approach for finding eligible PrEP candidates, therefore, increasing the relative efficiency of a more focused strategy for targeting PrEP at high-risk MSM attending STI clinics. When compared at equal levels of PrEP coverage (same number of people receiving PrEP), the relative impact of PrEP scenarios was only sensitive to reductions in HIV viral load (Panel C).Figure S9: Sensitivity analysis of PrEP impact in each scenario to variation of model parameters. The x-axis shows the percent difference in the estimated baseline impact of PrEP under the STI clinic-targeted scenario (targeting PrEP to STI clinic attendees, Panel A), and the untargeted (random) scenario (at equal level of screening- Panel B and equal number of PrEP initiation-Panel C) after a 20% change in the value of each parameter listed on the left. Each parameter value is followed by a +/- sign, denoting a 20% increase (+) or decrease (-) in the input parameter value. Input parameters for which such variation resulted in less than a 20% change in the corresponding output (HIV incidence or prevalence) are not shown.Sensitivity analysis to risk of HIV transmission among clinic attendeesSimilar to any other modeling study, our findings are limited to simplifying assumptions applied in development of the simulation model. In the absence of an explicit representation for other STIs triggering a new visit, we have adopted a simplified approach for modeling likelihood of MSMs’ presentation to the STI clinics after new partnerships formation. However, this approach may underestimate the presumably higher risk of HIV transmission among STI-clinic-attendees due to a combination of factor such as biological increase in risk of HIV transmission among those coinfected with other STIs, membership to high HIV/STI prevalent networks, individual-level risk factors, etc. As such, we have implemented an additional analysis to study the sensitivity of results to increased risk of HIV transmission among STI clinic attendees. Specifically, we developed a scenario in which the likelihood of presenting to STI clinic is modeled as a function of each individual’s (pre-assigned) sexual activity level, not just as a function of recent partnership formation. As noted earlier, our model uses a simplified definition of sexual activity classes (low, medium, high levels) to represent a combination of factors determining an individual’s tendency to engage in casual partnerships, with the aim of reflecting the diversity of sexual activity seen in real populations. By increasing the likelihood of STI clinic visits among the “high” sexual activity class (by a factor of 3, for purposes of illustration), those MSM who are marked by the model as the most likely to form partnerships in the future are also more likely to visit the STI clinic after forming new partnerships in the preceding week. After incorporating this feature, we recalibrated the model to generate a similar number of visits to the STI clinic in each year (~966 visits).In this new analysis (denoted in green in Figure S10), the number of MSM evaluated for PrEP was initially the same as in the baseline (denoted in red – see panel A), but because the MSM who are both eligible for PrEP and attending the STI clinic become more concentrated, there are fewer individuals who need to be evaluated for PrEP over time (panel B), but a larger number of MSM remain eligible for PrEP (panel C). This effect results in greater impact of PrEP on both incidence (panel D) and prevalence (panel E), assuming that individuals who are eligible for PrEP are successfully retained on PrEP. Figure S10: Sensitivity of the impact of STI-clinic targeted PrEP analysis to risk of HIV transmission among clinic attendees.These results confirm the sensitivity of the impact of the STI-clinic targeted PrEP on HIV incidence to underlying assumptions for presentation to STI clinic, and suggest that our primary findings may therefore be conservatively biased, to the extent that STI clinic attendance predicts higher sexual activity in the future. Furthermore, these results assume retention in PrEP care, which may be particularly challenging for this population; however, few data exist to inform the degree to which STI clinic attendance predicts future sexual activity. Sensitivity analysis to PrEP dropoutGiven existing evidence on patterns of medication discontinuation and program dropout among PrEP users in observational studies, and potential implications of this behavior on the population-level impact of PrEP, we have performed an additional sensitivity analysis that incorporates dropout from PrEP (as a weekly probability of PrEP discontinuation). In this analysis, MSM who discontinue PrEP are eligible to re-start PrEP in the future, as long as they present for screening and still meet eligibility criteria. We present these results in the figure below, with the solid line representing the current base case (no discontinuation), the dashed line representing a scenario with 0.5% dropout from PrEP per week, and the dotted line representing 1% dropout per week.Figure S11 presents the results in terms of absolute impact of STI-clinic targeted PrEP to variation in rate of dropout. Our results suggest that the absolute impact of PrEP is sensitive to variation in rate of dropout (Figure S11D and S11E). As more individuals discontinue PrEP, a smaller proportion of population is protected against HIV transmission and the overall impact on HIV incidence is reduced. However, given the similar impact of dropout rate on performance of community-based PrEP scenario, the relative impact of STI-clinic targeted PrEP compared to a community based approach is robust to variations in rate of dropout (Table S9).Figure S11: Sensitivity of the absolute impact of STI-clinic targeted PrEP to variation in rate of dropout.Table S9: Sensitivity of the relative impact of STI-clinic targeted PrEP compared to community-based approach at various levels of dropout.Drop out %(weekly)Relative difference between STI-clinic targeted PrEP and community-based scenario at equal level of screeningRelative difference between STI-clinic targeted PrEP and community-based scenario at equal level of screening0% (baseline)1.39 [1.34 - 1.46]1.97 [1.65 - 2.32]0.50%1.37 [1.27 - 1.48]2.17 [1.92 - 2.45]1%1.53 [1.32 - 1.75]1.95 [1.67 - 2.31] ReferencesADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY 1. Alliance BNI. Vital Signs 12 [Internet]. 2012. Available: . Maryland Department of Health and Mental Hygiene, MDHMH. 2012 Baltimore City Annual HIV Epidemiological Profile. Baltimore; 2012. 3. World Health Organization. Life tables by country United States of America. In: Global Health Observatory Data Repository [Internet]. 2013. Available: . Lieb S, Fallon SJ, Friedman SR, Thompson DR, Gates GJ, Liberti TM, et al. Statewide Estimation of Racial/Ethnic Populations of Men Who Have Sex with Men in the U.S. Public Health Rep. 2011;126: 60–72. 5. Beyrer C, Baral SD, van Griensven F, Goodreau SM, Chariyalertsak S, Wirtz AL, et al. Global epidemiology of HIV infection in men who have sex with men. Lancet. 2012;380: 367–77. 6. Marshall BD, Paczkowski MM, Seemann L, Tempalski B, Pouget ER, Galea S, et al. A complex systems approach to evaluate HIV prevention in metropolitan areas: preliminary implications for combination intervention strategies. PLoS One. 2012;7: e44833. 7. Escobar E, Durgham R, Dammann O, Stopka T. Agent-based computational model of the prevalence of gonococcal infections after the implementation of HIV pre-exposure prophylaxis guidelines. Online Journal of Public Health Informatics. 2015. doi:10.5210/ojphi.v7i3.61048. German D. BESURE Study: National HIV Behavioral Surveillance Study in Baltimore [Internet]. Available: . Beyrer C, Baral SD, van Griensven F, Goodreau SM, Chariyalertsak S, Wirtz AL, et al. Global epidemiology of HIV infection in men who have sex with men. Lancet. 2012;380: 367–77. 10. Vieira IT, Senna V de, Pereira. HB de B. A small world model for the spread of HIV infection. Pesqui Operacional. 2011;31: 373–389. 11. Egan JE, Frye V, Kurtz SP, Latkin C, Chen M, Tobin K, et al. Migration, neighborhoods, and networks: approaches to understanding how urban environmental conditions affect syndemic adverse health outcomes among gay, bisexual and other men who have sex with men. AIDS Behav. 2011;15: 35–50. 12. The INSIGHT START Study Group. Initiation of antiretroviral therapy in early asymptomatic HIV infection. N Engl J Med. 2015;373: 795–807. 13. Kitahata MM, Gange SJ, Abraham AG, Merriman B, Saag MS, Justice AC, et al. Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med. 2009;360: 1815–1826. 14. Palella Jr FJ, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. N Engl J Med. 1998;338: 853–860. 15. Rana AI, Liu T, Gillani FS, Reece R, Kojic EM, Zlotnick C, et al. Multiple gaps in care common among newly diagnosed HIV patients. AIDS Care. 2015;27: 697–687. 16. Sullivan PS, Peterson J, Rosenberg ES, Kelley CF, Cooper H, Vaughan A, et al. Understanding racial HIV/STI disparities in black and white men who have sex with men: a multilevel approach. PLoS One. 2014;9: e90514. 17. Hygiene MD of H and M. BESURE Study 2004-2014: Baltimore site of National HIV Behavioral Surveillance (NHBS) [Internet]. 2015. 18. Baggaley RF, Ferguson NM, Garnett GP. The epidemiological impact of antiretroviral use predicted by mathematical models: a review. Emerg Themes Epidemiol. 2005;2: 9. 19. Salomon JA, Hogan DR, Stover J, Stanecki KA, Walker N, Ghys PD, et al. Integrating HIV prevention and treatment: from slogans to impact. PLoS Med. 2005;2: e16. 20. Alam SJ, Meyer R, Norling E. A model for HIV spread in a South African village. Multi-Agent-Based Simul IX. 2009; 33–45. 21. Currie, S. KE, Rogstad AP, Herman. S. Time taken to undetectable viral load, following the initiation of HAART. Int J STD AIDS. 2009;20: 265–266. 22. Wit FW, Blanckenberg DH, Brinkman K, Prins JM, Ende ME van der, Schneider MM, et al. Safety of long-term interruption of successful antiretroviral therapy: the ATHENA cohort study. AIDS. 2005;19: 345–348. 23. Maggiolo F, Ripamonti D, Gregis G, Quinzan G, Callegaro A, Suter F. Effect of prolonged discontinuation of successful antiretroviral therapy on CD4 T cells: a controlled, prospective trial. AIDS. 2004;18: 439–446. 24. Ortiz GM, Wellons M, Brancato J, Vo HT, Zinn RL, Clarkson DE, et al. Structured antiretroviral treatment interruptions in chronically HIV-1-infected subjects. Proc Natl Acad Sci. 2001;98: 3288–13293. 25. El-Sadr WM, Lundgren JD, Neaton JD, Gordin F, Abrams D, Arduino RC, et al. CD4+ count-guided interruption of antiretroviral treatment. New Engl J Med. 2006;355: 2283–2296. 26. Marylan Department of Health and Mental Hygeine [Internet]. 2015. Available: . Prevention C for DC. Preexposure Prophylaxis for the Prevention of HIV Infection in the United States – 2014 Clinical Practice Guideline. 2014. 28. Singh S, Song R, Johnson AS, McCray E, Hall HI. HIV Incidence, HIV Prevalence, and Undiagnosed HIV Infections in Men Who Have Sex With Men, United States. Ann Intern Med. 2018; Additional references (Table1 in the main text)1S. Beyrer C, Baral SD, van Griensven F, Goodreau SM, Chariyalertsak S, Wirtz AL, et al. Global epidemiology of HIV infection in men who have sex with men. Lancet. 2012;380(9839):367–77. 2S. Baggaley RF, Ferguson NM, Garnett GP. The epidemiological impact of antiretroviral use predicted by mathematical models: a review. Emerg Themes Epidemiol. 2005;2(1):9. 3S. Salomon JA, Hogan DR, Stover J, Stanecki KA, Walker N, Ghys PD, et al. Integrating HIV prevention and treatment: from slogans to impact. PLoS Med. 2005 Jan 11;2(1):e16. 4S. Alam SJ, Meyer R, Norling E. A model for HIV spread in a South African village. Multi-Agent-Based Simul IX. 2009;33–45. 5S. Currie, S. KE, Rogstad AP, Herman. S. Time taken to undetectable viral load, following the initiation of HAART. Int J STD AIDS. 2009;20(4):265–6. 6S. Wit FW, Blanckenberg DH, Brinkman K, Prins JM, Ende ME van der, Schneider MM, et al. Safety of long-term interruption of successful antiretroviral therapy: the ATHENA cohort study. Aids. 2005;19(3):345–8. 7S. Maggiolo F, Ripamonti D, Gregis G, Quinzan G, Callegaro A, Suter F. Effect of prolonged discontinuation of successful antiretroviral therapy on CD4 T cells: a controlled, prospective trial. Aids. 2004;18(3):439–46. 8S. Ortiz GM, Wellons M, Brancato J, Vo HT, Zinn RL, Clarkson DE, et al. Structured antiretroviral treatment interruptions in chronically HIV-1-infected subjects. Proc Natl Acad Sci. 2001;98(23):3288–13293. 9S. El-Sadr WM, Lundgren JD, Neaton JD, Gordin F, Abrams D, Arduino RC, et al. CD4+ count-guided interruption of antiretroviral treatment. New Engl J Med. 2006;355(22):2283–96. 10S. The INSIGHT START Study Group. Initiation of antiretroviral therapy in early asymptomatic HIV infection. N Engl J Med. 2015;373:795–807. 11S. Kitahata MM, Gange SJ, Abraham AG, Merriman B, Saag MS, Justice AC, et al. Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med. 2009;360(18):1815–26. 12S. Palella Jr FJ, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. N Engl J Med. 1998;338(13):853–60. 13S. Rana AI, Liu T, Gillani FS, Reece R, Kojic EM, Zlotnick C, et al. Multiple gaps in care common among newly diagnosed HIV patients. AIDS Care. 2015;27(6):697–687. 14S. Baltimore City Health Department. HIV/STD Prevention Program. 2014. 15S. Centers for Disease Control Prevention. Preexposure Prophylaxis for the Prevention of HIV Infection in the United States – 2014 Clinical Practice Guideline. 2014. ................
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