Knowledge attitude & Practice survey protocol



centercenterAdamu YerimaUNICEF??[Company address]Knowledge attitude & Practice survey protocol8820090900Adamu YerimaUNICEF??[Company address]Knowledge attitude & Practice survey protocolTable of Content TOC \o "1-5" \h \z \u Table of Content PAGEREF _Toc43734253 \h 11Justification PAGEREF _Toc43734254 \h 22Current Status / Available Information PAGEREF _Toc43734255 \h 23Objectives PAGEREF _Toc43734256 \h 34Methodology PAGEREF _Toc43734257 \h 34.1Qualitative Data Collection PAGEREF _Toc43734258 \h 34.1.1Sampling, Data Collection & Analysis PAGEREF _Toc43734259 \h 44.2KAP Survey PAGEREF _Toc43734260 \h 44.2.1Study Design PAGEREF _Toc43734261 \h 54.2.2Sample Design PAGEREF _Toc43734262 \h 54.2.2.1First stage sampling procedure: cluster selection PAGEREF _Toc43734263 \h 64.2.2.2Second stage sampling procedure: household selection PAGEREF _Toc43734264 \h 64.2.2.2.1Segmentation PAGEREF _Toc43734265 \h 64.2.2.3Sample size determination PAGEREF _Toc43734266 \h 65Indicators PAGEREF _Toc43734267 \h 106Personnel & Collaboration PAGEREF _Toc43734268 \h 127Training PAGEREF _Toc43734269 \h 128Fieldwork Plan PAGEREF _Toc43734270 \h 139Data Collection and Supervision PAGEREF _Toc43734271 \h 139.1Field Testing of Instrument PAGEREF _Toc43734272 \h 139.2Field Data Collection PAGEREF _Toc43734273 \h 1310Data Quality Control and Data Entry PAGEREF _Toc43734274 \h 1410.1Data quality control PAGEREF _Toc43734275 \h 1410.2Data entry PAGEREF _Toc43734276 \h 1511Analysis and Report Writing PAGEREF _Toc43734277 \h 1512Dissemination PAGEREF _Toc43734278 \h 1513Anticipated limitations and potential biases PAGEREF _Toc43734279 \h 15Annex 1: Implementation timeline PAGEREF _Toc43734280 \h 17References PAGEREF _Toc43734281 \h 18 JustificationThe humanitarian crisis in North-East Nigeria has become protracted, with the populace bearing the brunt of the conflict that has resulted in widespread displacement, destroyed infrastructure and collapsed basic social services. Threats of attacks by non-state armed groups and restrictions in movements continue to have negative impacts on trade, livelihoods and markets, leaving a substantial proportion of the population relying on humanitarian assistance. As at November 2019, 2,035,232 people are still displaced in the three most affected states - Borno, Adamawa and Yobe (BAY) States – with 80 percent of the displaced population being women and children. A total of 7.9 million people representing more than half of the population of BAY states are in need of humanitarian assistance in 2020.Despite difficulties to access many LGAs in Borno state, an intense multi-sector emergency response has been mounted since the beginning of 2016 when newly accessible areas were entered by government and humanitarian partners. The emergency response includes establishment of IDP camps, distribution of food and non-food items, WASH interventions, EPI and Polio and nutrition interventions. Humanitarian partners have been responding to the protracted emergencies and have scaled-up services to affected populations significantly since the declaration of emergency in 2016. Amongst the programs being implemented are water, sanitation and hygiene (WASH), nutrition and health amongst others. This has necessitated the need to use a data-driven approach in decision making. Thus, the need to implement knowledge, attitude and practice (KAP) study as both a situation analysis tool when developing new interventions as well as outcome evaluation tool.A KAP study or survey is a representative study of a specific population to collect information on what is known, believed and done in relation to a specific topic — in this case for WASH, nutrition, health and protection issues. KAP surveys can identify knowledge gaps, cultural beliefs, or behavioural patterns that may facilitate understanding and action, as well as pose problems or create barriers for program implementation as well as results. KAP provides fundamental information that can be used to make strategic decisions and is a critical component in the project monitoring and evaluation framework already in place.Current Status / Available Information Currently, partners have been implementing stand-alone KAP surveys using differing methodologies and sampling designs. As part of the sector-wide strategy to standardize and harmonize data collection system ensuring synergy and inter-sectoral collaboration, it was agreed that state-wide KAP survey is not out of place. This will standardize the data collection process and harmonize the indicators. In order to continue to monitor the humanitarian situation and response, a state-wide KAP surveys representative at LGA level is proposed. The survey will use similar methods to ensure comparability and allow partners to monitor health, nutrition, WASH, food security and child protection/gender based violence outcomes. Objectives The main objective of the KAP study is to identify knowledge gaps, cultural beliefs, or behavioural patterns that may facilitate understanding and action. They can also assess communication processes and sources that are critical to defining effective activities as well as highlight issues and barriers in programme delivery, and solutions for improving quality and accessibility of services. To describe the population’s knowledge, attitude and practice status, with reference to, women and children. To develop the data base for Health, WASH, Nutrition and Child protection in NE for reference and for validation of program informationTo facilitate decision making processes for program by Government and Humanitarian partners on how best to meet the needs populations in emergency.To understand the KAP during Covid19 to realign the program and strategic directions Methodology The survey will utilize a mixed-methods approach; obtaining both quantitative and qualitative data by utilizing two distinct methodologies of Qualitative Data Collection (qualitative method) and KAP surveys (quantitative methods) to enable us to measure the overall goal of the survey and its specific objectives. Qualitative Data Collection The qualitative data collection will utilize Focus Group Discussions (FGD) with beneficiaries and other stakeholders in the community, Semi-Structured Interviews (SSI) with traditional rulers, Community Nutrition Mobilizers (CNM), WASH volunteers and traditional healers, then finally In-Depth Interview (IDI) with hygiene promoters, health care workers, and program staff. Information generated will be used enumerate the likely causes of malnutrition, barriers to child health and the prevailing nutrition and hygiene practices in the project areas. These together with the data from the quantitative techniques to will be utilized to ascertain the efficiency and effectiveness of the current nutrition program. The details of each methodology are as below:Focus Group Discussions: in this data collection technique, beneficiaries between 8 – 12 will be gathered in the same place and the 2 interviewers (1 facilitator and 1 qualitative note taker) will guide the discussion using the FGD discussion guide to get all the information from the relevant stakeholders in the community on how and why the interventions are working or not. As a rule of thumb, 2 group discussions should be conducted per type of respondent.Semi-Structured Interviews: where it is not possible to gather 8 – 12 persons or for a category of stakeholders such as traditional rulers, traditional healers and CNM or VCM in the communities visited, a one-on-one SSI will be conducted using the interview guide.In-Depth Interviews: this will be conducted with stakeholders with in-depth knowledge about the program or intervention to gain the experts view about the program. It is also conducted one-on-one using an interview guide or questionnaire. The targeted stakeholders for this methodology are the HCW and the project/ program staff.Sampling, Data Collection & AnalysisIn qualitative methodology, the sampling, data collection and analysis follow an iterative process that involves collecting data, focusing on the data and analyzing the data continuously (Figure 1) until when no new information is obtained from the field a phenomena refer to as ‘Sampling to Redundancy’ or ‘Sampling to Saturation’. The data obtained is analyzed by focusing on the data after transcribing the interview or discussion notes and or recordings. The data is focused on to remove irrelevant and un-important part of the interview and concentrate on the relevant and important information through coding and identifying themes or concepts within the data with subsequent margin to higher level categories and or theme. TimeTimeFigure SEQ Figure \* ARABIC 1. Sequence of qualitative research CITATION Lof06 \l 1033 (Lofland, Lofland, Snow, & Anderson, 2006)KAP SurveyA KAP survey is a quantitative assessment that use a predefined question formatted in a standardized questionnaire. KAP survey reveal misunderstandings that may represent obstacles to the activities that we would like to implement and potential barriers to behavior change and program improvement. The questionnaire that was used for the baseline estimate will be utilized to allow for comparison between the baseline and the endline surveys. Study Design The survey is designed as a cross-sectional household survey using a two-stage cluster sampling representative at LGA level. The survey area consists of 23 accessible LGAs of, Borno state. The 65 LGAs are divided into 10 domains; 2 in Adamawa, 3 in Yobe and 5 in Borno states.The list of LGAs and estimated populations is as provided in the table below. Table SEQ Table \* ARABIC 1: List of LGAs with Estimated PopulationsStateLGAPopulationBornoAskira/Uba275,171BornoBama195,424BornoBayo167,823BornoBiu326,333BornoChibok131,734BornoDamboa166,014BornoDikwa117,618BornoGubio180,569BornoGwoza273,202BornoHawul252,553BornoJere729,629BornoKaga125,459BornoKala/Balge116,985BornoKonduga237,739BornoKwaya Kusar135,655BornoMafa117,733BornoMagumeri274,444BornoMaiduguri904,158BornoMobbar175,015BornoMonguno211,979BornoNgala130,654BornoNganzai147,991BornoShani230,119The actual representativeness of each of the LGA results will depend on the accessibility of the wards/settlements at the time of the assessment. The aggregated data at state level allows further comparison of results from this result and will be computed using a weighting analysis. Sample DesignAdministratively Nigeria is divided into states and each state is sub-divided into Local Government Areas (LGAs), and each LGA is divided into wards. In addition to these administrative units, during the 2006 population census, each locality was subdivided into census Enumeration Areas (EAs). The sample was selected using a two-stage cluster design. The clusters for each domain were drawn independently using probability proportional to size (PPS) method. Given recent large-scale population movement, an updated sampling frame was built for Borno. A list of lowest possible unit (villages or camps) available will be used for sampling. Population estimates from the January 2019 polio campaign micro plan as well as VTS population estimates by settlement was used for settlements. Settlements that have less than 20HHs will all be sampled and the remaining HHs supplemented from nearest villages (within 5KM radius of the selected village). Population estimates for internally displaced persons (IDP) camps will be used from the latest International Organization on Migration (IOM) Displacement Tracking Matrix (DTM) report available at the time of the survey (DTM Round XXIX, November 2019). In-accessible areas will be excluded a priori. Accessibility will be determined by state level security officers and informed by access during the most recent polio campaign. First stage sampling procedure: cluster selection The sample will be selected using a two-stage cluster design. The PSU (clusters) will be randomly selected according to the probability proportional to size (PPS) method.To avoid unforeseen challenges to access the selected clusters during data collection reserve clusters will be selected at this sampling stage using fractional interval systematic sampling. The reserve clusters will only be used as replacement when original clusters were not reachable during data collection. All reserve clusters will be surveyed if the reserve clusters are needed.Second stage sampling procedure: household selectionThe second stage of sampling consists of selecting households within each cluster by using systematic random selection. The team will determine the total number of households in the cluster by completing a household listing of the selected cluster with the support from the community leader. This will serve as the sampling frame for household selection. The households to be sampled are selected using the same fractional interval systematic random sampling.SegmentationIn a situation where the selected cluster is too large or more than was cluster was selected for a particular settlement or EA, the team under the supervision of a supervisor or coordinator need to divide the cluster and sub-sample a part of it in a process known as ‘Segmentation’. Any cluster that has exceeds 300 households should be segmented.Sample size determination The sample sizes for WASH/Child protection at household level were calculated using the sample size estimation for educational assessment as proposed by Krejcie & Morgan (1970), while the IYCF sample sizes (exclusive breast feeding for children 0-5 months and complementary feeding for children 6-23 months) were calculated using the USAID Feed the Future Population-based Sampling Guide. These were used as the primary indicators and have been calculated using the following formulas;For WASH indicators at household levels;n=X2NP1-Pd2N-1+X2P1-Pn=required sample sizeX2=3.841N=population sizeP=population proportion or expected prevalenced=degree of accuracy or margin of error=0.05While for IYCF & Health indicators the following formulae was used for individuals;n=z1-α2. P1-Pd2z1-α=1.96→ z1-α2=3.841 P=estimated population proportion or expected prevalenced=degree of accuracy or margin of errorHowever, there is a need to convert the number of individuals calculated to number of households required to reach those individuals. Thus, the following formulae was used to do the conversion;NHH =NChildren(Average HH Size×% of Target Age group)NHH =number of households requiredNChildren=sample size of children requiredAverage HH Size=average household size% of Target Age group=proportion of the target age group in the populationAnd the result was as presented in the table below:Table SEQ Table \* ARABIC 2 Anthropometry & mortality sample size inputsLGAPopulationIn-Accessible PopulationAccessible PopulationAverage Household SizeEBF Rate (children 0-5 Months)MDD Rate (children 6-23 Months)Sample SizeHouseholdChildren 0-5 monthsChildren 6-23 monthsChildrenHouseholdChildrenHouseholdAbadam42,354 25,039 17,315 ????Guzamala82,892 76,386 6,506 Kukawa110,587 52,987 57,600 ???Mobbar175,015118,861 56,154 5.946.40%7.00%38679669 101 285 Nganzai147,991 57,857 90,134 5.9 46.40%7.00%38679669 101 285 Askira/Uba275,171 52,359 222,812 5.7 56.70%19.30%38678684 240 702 Bayo167,823-167,823 5.7 56.70%19.30%38678684 240 702 Biu326,333 12,960 313,373 5.7 56.70%19.30%38678684 240 702 Chibok131,7344,925 126,809 5.7 56.70%19.30%38678684 240 702 Hawul252,553-252,553 5.7 56.70%19.30%38678684 240 702 Kwaya Kusar135,655-135,655 5.7 56.70%19.30%38678684 240 702 Shani230,119-230,119 5.7 56.70%19.30%38678684 240 702 Bama195,424 78,023 117,401 5.8 57.00%19.50%38678672 242 695 Dikwa117,618 22,308 95,310 5.8 57.00%19.50%38678672 242 695 Gwoza273,202 59,274 213,928 5.8 57.00%19.50%38678672 242 695 Kala/Balge116,9857,306 109,679 5.8 57.00%19.50%38678672 242 695 Ngala130,6549,673 120,981 5.8 57.00%19.50%38678672 242 695 Marte24,2829,359 14,923 ????Damboa166,014 16,941 149,073 5.6 37.50%4.20%38679705 62 185 Gubio180,569143,398 37,171 5.6 37.50%4.20%38679705 62 185 Kaga125,459 63,112 62,347 5.6 37.50%4.20%38679705 62 185 Konduga237,739 14,101 223,638 5.6 37.50%4.20%38679705 62 185 Mafa117,733 17,226 100,507 5.6 37.50%4.20%38679705 62 185 Magumeri274,444114,514 159,930 5.6 37.50%4.20%38679705 62 185 Monguno211,979 11,703 200,276 5.6 37.50%4.20%38679705 62 185 Jere729,6293,804 725,825 5.6 45.30%8.80%38679705 124 369 Maiduguri904,158-904,158 5.6 45.30%8.80%38679705 124 369 Total5,884,117 972,116 4,912,001 5.7 45.60% 9.20% 10,422 2,579 16,2264,16110,990The highest sample size for WASH/Child Protection (using 50% prevalence for the worst-case scenario) or for IYCF (using EBF rate and or minimum dietary diversity rate from NE_NFSS round 8 results) is considered for the survey to be able get highest possible precision. Considering the time the team needs for household listing, household selection, interview and travel to the EAs into account, it was determined to complete 20 households or less by a team per cluster per day which resulted in selection the following clusters per LGA (see the table below). LINK Excel.Sheet.12 "C:\\Users\\ayerima\\Documents\\KAP Survey Sample Size Calculations.xlsx" "Sampling Design!R38C1:R62C4" \a \f 4 \h \* MERGEFORMAT LGAHouseholds / LGAClusters / LGAHouseholds / ClusterMobbar 669 33 20Nganzai 669 33 20Askira/Uba 702 35 20Bayo 702 35 20Biu 702 35 20Chibok 702 35 20Hawul 702 35 20Kwaya Kusar 702 35 20Shani 702 35 20Bama 695 34 20Dikwa 695 34 20Gwoza 695 34 20Kala/Balge 695 34 20Ngala 695 34 20Damboa 705 35 20Gubio 705 35 20Kaga 705 35 20Konduga 705 35 20Mafa 705 35 20Magumeri 705 35 20Monguno 705 35 20Jere 705 35 20Maiduguri 705 35 20Total 16,076 796 ?IndicatorsThe following indicators are proposed to be included in the surveillance program:WASH – collected at household level and are indicators of water quantity, water access, water quality, sanitation and hygiene. The indicators are;Average number of litres of potable water per person per day collected per householdPercentage of households with at least 15 litres per person of protected water storage capacityPercent of people who received and shown understanding of improved service quality from solid waste management, drainage, or vector control activities.Percent of people targeted by the hygiene promotion program who know at least three (3) of the five (5) critical times to wash handsPercent of households targeted by the hygiene promotion program who store their drinking water safely in clean containersPercent of people targeted by the hygiene promotion program who report using a latrine the last time they defecated.Percentage of households collecting drinking water from protected/treated sourcesPercentage of households with family latrine or toiletPercentage of households reporting defecating in a toilet or latrinePercent of households in the target population with handwashing facilities that are functional and in usePercentage of households practising open defecationPercentage of recipient women of reproductive age who are satisfied with their menstrual hygiene management materials and facilitiesPercent of water user committees created and/or trained by the WASH program that are active at least three (3) months after trainingPercent of water points developed, repaired, or rehabilitated that are clean and protected from contaminationNutrition Percent of children 0-5months receiving exclusive breastfeedingPercent of children 6-23moths receiving 4 or more food groups (MDD)Percent of children 6-23months receiving minimum meal frequencyPercent of children 0-23months receiving appropriate breastfeeding practicePercent receiving early initiation of breastfeeding within one hourPercent receiving continuous breastfeeding at 1 yearPercent receiving continuous breastfeeding at 2 yearsPercent of caregivers with understanding of the benefits of breastfeedingKnowledge of early initiation of breastfeedingKnowledge of exclusive breast feedingKnowledge of continuous breastfeeding at 1 yearKnowledge of continuous breastfeeding at 2 yearsPercent of caregivers with knowledge of reasons for diets of young childrenPercent of caregivers with belief in benefits of dietary diversity (perceived benefits)Percent of caregivers with preference for targeted foodsPercent of women of childbearing age (WCBA) receiving 4 or more food groups (WMDD)Percent of women of childbearing age (WCBA) receiving iron rich foodsPercent of children 6-59months receiving vitamin A supplementation (VAS)Percent of pregnant women receiving iron folate (FeFo)% of Families and mothers to have MUAC for screening of children with SAM% of mothers left breast feeding to children below 6 months because of Covid19% of mothers and families have stopped feeding children 6-24-month olds% of families are able to use the MUAC for screening of children at homeHealthRate of delivery by skilled birth-attendant Rate of ANC visits.Health seeking behaviour and walking distance to health facilitiesKnowledge and prevention of common rural communicable diseaseEstimated prevalence of child morbidity (Two-week recall)Child Protection % of households reporting children living with people who are not their biological parents of their regular caregivers in their community.% of households reporting children without parents living on their own without any parents/adults caregivers in their community% of households reporting children neglected and roaming around in the community during school hours% of households reporting children hawking or begging on the streets during school hours% of households reporting girls are married before the age of 18 years in their community.% of households reporting maltreatment of children by their parents or caregivers including beating and other forms of physical abuse in their community.% of households reporting neglect and abuse of children because of their disabilities or special needs in their communityKnowledge and practices on what to do if aware of serious child abuse??Covid-19% of households practicing appropriate COVID-19 infection, prevention and control measuresPersonnel & CollaborationCollaboration The survey will be implemented in a multi-sectoral and multi-partner approach. The WASH, Nutrition, Health and Child Protection sectors as well as partners will be involved. The implementation approach is such that UNICEF (WASH & Nutrition sections) and Nutrition sector will lead development, planning, training and field data collection not covered by partners. While the partners will lead the implementation in their focus LGAs using the same tools and on the same server managed by UNICEF.Recruitment and team organizationThe National Bureau of Statistics (NBS) together with National Population Commission (NPopC) and Federal Ministry of Health (FMOH) will identify people to be involved in the survey in areas where UNICEF will implement. While on the other hand, in areas where partners will implement, the selection will vary based on internal processes of partners.The candidates will be selected based on their experience in surveys and language skills in order to interview the respondents in their native language as much as possible. English language ability is required for all team members. All enumerators should be a female and should wear culturally appropriate clothes in order not to be refused to undertake the work by the household as men are not allowed to enter household to measure children and women. TrainingThe interviewer’s training will last for 3 days in Maiduguri. The training will include the following:An overview of the survey and its objectives, Interviewing and general communication skillsContextualising the questionnaire into the local contextSystematic random selection of households and segmentationIdentification of individuals to measure or interviewHow to complete the questionnaires using tablets Correct age estimation in months and validation using the calendar of local eventsA pilot test will be conducted before the commencement of data collection. This will be used as an opportunity to assess the tools and evaluate the actual data collection process before deployment of the teams. Feedbacks from the pilot test will be discussed and addressed before actual data collection. Partners will nominated their staff for the training, who can then cascade the training for their partner specific enumerators. Fieldwork PlanThe data collection exercise will take approximately 3 weeks. The enumerators for the survey will be assessed during the training and continually throughout the data collection period. Only those teams who are consistently producing high quality data will be retained. If the data quality of a team is found to be unacceptable, their employment will end immediately. The small number of team per group will allow the supervision teams to provide effective support by reviewing the skills and implementation of all data collection process during entire period. Detailed fieldwork plan will be created to visit the most remote selected enumeration areas within the state first. This will avoid missing of selected clusters in the area due to inaccessibility from rain or impassable roads. The team constitutes of experienced and senior staffs from National Bureau of Statistics, National Population Commission and Federal Ministry of Health. UNICEF will provide technical support and supportive supervision throughout the entire process. Data Collection and Supervision Field Testing of InstrumentThe scripted questionnaire will be field tested for validation and calculation of fieldwork duration (duration of questionnaire administration per household and per cluster per day). The field testing will be conducted by a team of enumerators (similar in experience and skills with those that will conduct the field data collection) under the supervision of the survey manager.Field Data CollectionSamsung Galaxy tab 4 7.0” or Galaxy Tab A6 will be used to collect data in the field. The questionnaires will be developed in ODK and hosted on the ONA (Ona.io). The data will automatically be sent to central server using 3G internet connection. Once, the data was received it will be analysed daily for key quality checks. This will serve as the basis for communication between the coordinator and the rest of the survey teams during entire data collection period.Prior to the start of the data collection phase of the survey, the selected LGA authorities will be informed about the survey in order to communicate with the community that the data collection will take place in the area. This will help to gain support from the officials and the community during the data collection. Each team has its own vehicle and is accompanied by a driver.The supervisor is in overall charge of a group. A group consists of 3 teams that cover an average 2 LGAs. He/she is responsible for the daily organization and supervision of the team’s work. He/she assigns work to the team members, responsible for logistic arrangements and where possible also helps the team in locating accommodation. Additionally, he/she is also responsible for checking the quality of the interview by observing the interview and anthropometric measurements.The Coordinators are responsible to support supervisors to ensure that all necessary arrangements are made before the arrival of the team to states and provide other support based on need. They also support the daily activities of the team based on feedback received from survey manager using data that will be sent to the central server on daily basis. The coordinator in collaboration with the supervisors should identify and support the team that needs more support thereby to improve the overall quality of the survey. The survey teams will start fieldwork in the same location following training in order to make supervision of all teams by senior survey staff possible during the time that supervision is most needed. To ensure that the travel times from one cluster to the other are minimized as much as possible, the team are also advised to stay in the nearest local government area (LGA). Data Quality Control and Data Entry Data quality controlTo ensure the quality of data, supportive supervision will be provided for the team at different level. The first level of supervision is provided by the team supervisors who are responsible for closely monitoring the work of the teams to ensure that all sampled households are visited, and eligible children and women are included. An important element of this supervision is to periodically return to few selected households and conduct a short re-interview of listing of household members and comparing the list with what was reported originally by the team. The main aim of such re-interviews is to uncover any deliberate distortion of age or omission of household members by interviewers so as to reduce their workload. They will also observe the interview to ensure that the survey team are conducting the interviews as per the interview manual. The second level of supervision consists of coordinators and state level government officers visit to the field. It is expected that the coordinators and other qualified staffs from state offices will visit teams on regular basis to check on their work. Strengths and weaknesses will be discussed in review session with the teams.A daily review summarizing key quality issues will be provided to the teams during fieldwork to check the data that was sent using smart phone (tablets). The review will look at issues such as response rates, the age distribution of children, women and household members, the level of missing values for key indicators, time of data collection and quality of anthropometric measurements if any. Any problems that appear from the review will be discussed with the appropriate teams and attempts will be made to ensure that they do not persist. Data entryThe data will be collected using 3G enabled tablets. Therefore, data collection and data entry will be completed at the same time in the field. This will help to facilitate quick review with the objective to improve the quality of data and real time reporting of the results. In addition to saving the time of data entry it will also help to save money that would have otherwise been spent on second round data entry and validation process.COVID-19 IPC Measures for Training and Data CollectionEnumerators and supervisors will be tested for COVID-19, only negative will be employed/engagedWearing of masks, individual sanitizers etcSocial distancing during data collection, training etc. No hand greetings when visiting household etcFGD and other grouping will adhere to social/physical distancing No sharing of pens etcVehicles sanitised/decontaminated everydayApproval by SPHCDA Proper training of enumerators on COVID IPCetcAnalysis and Report Writing The analysis will be completed within a week following completion of data collection. A brief summary report (anthropometry & mortality data only) of the survey will be made available by the end of 2 weeks following completion of data collection. The results will be presented in the standard format. This format includes estimates with 95% confidence intervals. The report will have estimates for standards indicators. The data quality report will be included in the data quality section of the report. The summary and final report will be made available by the end of August 2020. Stata version 14.0 will be used for analysis of survey data. To account for ongoing, large scale population movement, cluster level weights will be calculated adjusting for selection probability within the cluster and non-response, as described by Brogan et al., 1994.DisseminationDissemination of the survey results to all relevant audience will be conducted both at state and national level. This is to ensure that survey results are used for better programing and to encourage demands for future surveys. The results will be circulated as widely as possible and will also be available for downloading on the National Bureau of Statistics (NBS) and relevant humanitarian website. Partners will be responsible for their dissemination process as well as audience.Anticipated limitations and potential biases13.1. Reliability of the sampling frameThe Master sampling frame used for the random selection of Primary Sampling Units (Enumeration Areas) was built in 2005. As the projections at EA levels are technically difficult to obtain, the choice is made to use the original population estimates for the cluster selection when applying the PPS method. Additionally, in areas with population movement it is expected to have reliable data from states, VTS and DTM report. The reliability of these data can bias the outcome. 13.2. Reliability of the EA mapsThe mapping of the enumeration areas dated from 2006 census, which means that the boundaries might have changed since then. Boundaries for PSU in areas with significant population movement will be a big challenge. 13.3. AccessibilityAlbeit the road accesses and travel conditions are still acceptable, it is anticipated that, this situation may change due to different reasons. Annex 1: Implementation timeline ActivitiesJune 2020July 2020August 2020W1W2W3W4W1W2W3W4W1W2W3W4Planning the survey ????????Updating indicators based on previous rounds and current needs????????Engage partners for support????????Review and update survey protocol ???????Planning and budgeting activities ????????Organizing logistics????????Sampling and printing of EA maps ????????Developing survey tools ????????Developing electronic data collection tools ????????Programing of tablets????????Pretest the application of tablets/Field testing Developing training manual ????????Training and Implementation ????????Recruiting field staffs???????TrainingField data collectionData Cleaning, Analysis & Reporting????????Data cleaning and analysis ????????Prepare draft summary report????????Share final summary report????????Prepare final reportDissemination????????References BIBLIOGRAPHY Lofland, J., Lofland, L. H., Snow, D. A., & Anderson, L. (2006). A guide to qualitative observation and analysis (4th Edition ed.). Belmont, CA, USA: Wadsworth Publishing Company,.Brogan D, Flagg EW, Deming M, Waldman R. Increasing the accuracy of the Expanded Programme on Immunization's cluster survey design. Ann Epidemiol. 1994 Jul; 4(4):302-11. ................
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