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Disaggregated population counts are needed to calculate health, economic, and development indicators in Low- and Middle-Income Countries (LMICs), especially in settings of rapid urbanisation. Censuses are often outdated and inaccurate in LMIC settings, and rarely disaggregated at fine geographic scale. Modelled gridded population datasets derived from census data have become widely used by development researchers and practitioners. These datasets are evaluated for accuracy at the spatial scale of the input data which is often much courser (e.g. administrative units) than the neighbourhood or cell-level scale of many applications. We simulate a realistic "true" 2016 population in Khomas, Namibia, a majority urban region, and introduce realistic levels of outdatedness (over 15 years) and inaccuracy in slum, non-slum, and rural areas. We aggregate these simulated realistic populations by census and administrative boundaries (to mimic census data), and generate 32 gridded population datasets that are typical of a LMIC setting using WorldPop-Global-Unconstrained gridded population approach. We evaluate the cell-level accuracy of these simulated datasets using the original "true" population as a reference. In our simulation, we found large cell-level errors, particularly in slum cells, driven by the use of average population densities in large areal units to determine cell-level population densities. Age, accuracy, and aggregation of the input data also played a role in these errors. We suggest incorporating finer-scale training data into gridded population models generally, and WorldPop-Global-Unconstrained in particular (e.g., from routine household surveys or slum community population counts), and use of new building footprint datasets as a covariate to improve cell-level accuracy. It is important to measure accuracy of gridded population datasets at spatial scales more consistent with how the data are being applied, especially if they are to be used for monitoring key development indicators at neighbourhood scales with relevance to small dense deprived areas within larger administrative units.

BACKGROUND:PrePex Male Circumcision (MC) has been demonstrated as an effective and scalable strategy to prevent HIV infection in low- and middle-income countries. This study describes the follow-up and outcomes of clients who underwent PrePex MC between January 2011 and December 2012 with weekly follow-up at the Rwanda Military Hospital, the first national hospital in Rwanda to adopt PrePex.METHODS:Data on 570 clients age 21 to 54 were extracted from patient records. We compared socio-demographic and clinical characteristics, the operator's qualification, HIV status, pain before and after device removal, urological status, device size and follow-up time between clients who were formally discharged and those who defaulted. We reported bivariate associations between each covariate and discharge status, number of people with adverse events by discharge status, and time to formal discharge or defaulting using life table methods. Data were entered into Epidata and analyzed with Stata v 13.RESULTS:Among study participants, 96.5% were circumcised by non-physician operators, 85.4%were under 30 years, 98.9% were HIV-negative and 97.9% were without any urological problems that could delay the healing time. Most (70.7%) defaulted before formal discharge. Pain before (pCONCLUSION:Given that all socio-demographic and most clinical characteristics were not associated with defaulting, we hypothesize that clients stopped returning once they determined they were healed. We recommend less frequent follow-up protocols to encourage clinical visits until formal discharge. Based on these results and recommendations, we believe PrePex MC is a practical circumcision strategy in Rwanda and in sub-Saharan Africa.

BACKGROUND:We devised and implemented an innovative Location-Based Household Coding System (LBHCS) appropriate to a densely populated informal settlement in Mumbai, India.METHODS AND FINDINGS:LBHCS codes were designed to double as unique household identifiers and as walking directions; when an entire community is enumerated, LBHCS codes can be used to identify the number of households located per road (or lane) segment. LBHCS was used in community-wide biometric, mental health, diarrheal disease, and water poverty studies. It also facilitated targeted health interventions by a research team of youth from Mumbai, including intensive door-to-door education of residents, targeted follow-up meetings, and a full census. In addition, LBHCS permitted rapid and low-cost preparation of GIS mapping of all households in the slum, and spatial summation and spatial analysis of survey data.CONCLUSION:LBHCS was an effective, easy-to-use, affordable approach to household enumeration and re-identification in a densely populated informal settlement where alternative satellite imagery and GPS technologies could not be used.

BACKGROUND: In 2012, 6.6 million children under age five died worldwide, most from diseases with known means of prevention and treatment. A delivery gap persists between well-validated methods for child survival and equitable, timely access to those methods. We measured early child health care access, morbidity, and mortality over the course of a health system strengthening model intervention in Yirimadjo, Mali. The intervention included Community Health Worker active case finding, user fee removal, infrastructure development, community mobilization, and prevention programming.METHODS AND FINDINGS: We conducted four household surveys using a cluster-based, population-weighted sampling methodology at baseline and at 12, 24, and 36 months. We defined our outcomes as the percentage of children initiating an effective antimalarial within 24 hours of symptom onset, the percentage of children reported to be febrile within the previous two weeks, and the under-five child mortality rate. We compared prevalence of febrile illness and treatment using chi-square statistics, and estimated and compared under-five mortality rates using Cox proportional hazard regression. There was a statistically significant difference in under-five mortality between the 2008 and 2011 surveys; in 2011, the hazard of under-five mortality in the intervention area was one tenth that of baseline (HR 0.10, pCONCLUSIONS: Community-based health systems strengthening may facilitate early access to prevention and care and may provide a means for improving child survival.

BACKGROUND:Disability affects approximately 15% of the world's population, and has adverse socio-economic effects, especially for the poor. In Rwanda, there are a number of government compensation programs that support the poor, but not specifically persons with disability (PWDs). This study investigates the relationship between poverty and government compensation on disability among working-age adults in Rwanda.METHODS:This was a secondary analysis of 35,114 adults aged 16 to 65 interviewed in the 2010/2011 Rwanda Household Wealth and Living Conditions survey, a national cross-sectional two-stage cluster survey, stratified by district. This study estimated self-reported major disability, and used chi-square tests to estimate associations (pRESULTS:Over 4% of working-age adults reported having a major disability and the most prevalent types of disability in order were physical, mental, and then sensory disability. In bivariate analysis, annual income, occupation type, and poverty status were associated with major disability (pCONCLUSION:Given that personal income rather than government programming is associated with disability in Rwanda, we recommend deliberately targeted services to those with disability via cash transfers, placements in disability-appropriate employment, and micro-savings programs.