The Effect of Distance to Formal Health Facility on Childhood Mortality in Rural Tanzania, 2005-2007.

Major improvements are required in the coverage and quality of essential childhood interventions to achieve Millennium Development Goal Four (MDG 4). Long distance to health facilities is one of the known barriers to access. We investigated the effect of networked and Euclidean distances from home to formal health facilities on childhood mortality in rural Tanzania between 2005 and 2007. A secondary analysis of data from a cohort of 28,823 children younger than age 5 between 2005 and 2007 from Ifakara Health and Demographic Surveillance System was carried out. Both Euclidean and networked distances from the household to the nearest health facility were calculated using geographical information system methods. Cox proportional hazard regression models were used to investigate the effect of distance from home to the nearest health facility on child mortality. Children who lived in homes with networked distance>5 km experienced approximately 17% increased mortality risk (HR=1.17; 95% CI 1.02-1.38) compared to those who lived <5 km networked distance to the nearest health facility. Death of a mother (HR=5.87; 95% CI 4.11-8.40), death of preceding sibling (HR=1.9; 95% CI 1.37-2.65), and twin birth (HR=2.9; 95% CI 2.27-3.74) were the strongest independent predictors of child mortality. Physical access to health facilities is a determinant of child mortality in rural Tanzania. Innovations to improve access to health facilities coupled with birth spacing and care at birth are needed to reduce child deaths in rural Tanzania

Prevalence and risk factors for child labour and violence against children in Egypt using Bayesian geospatial modelling with multiple imputation

Background The incidence of child labour, especially across developing nations, is of global concern. The use of children in employment in developing economies constitutes a major threat to the societies, and concerted efforts are made by the relevant stakeholders towards addressing some of the factors and issues responsible. Significant risk factors include socio-demographic and economic factors such as poverty, neglect, lack of adequate care, exposure of children to various grades of violence, parental education status, gender, place of residence, household size, residence type or size, wealth index, parental survivorship and household size. Egypt is the largest country in Africa by population. Although UNCIF 2017 reported that the worst forms of child labour in Egypt are concentrated in domestic work, forced begging and commercial sexual exploitation, the situation has received little attention. There are still very few studies initiated specifically to look at child labour in domestic service in Egypt and those that exist have been limited in the scope of their methodology. Geographical coverage and research for child labour in Egypt is also limited, as are accurate statistics and data. There was, therefore, a strong case for looking again at the domestic child labour phenomenon in Egypt, especially after the Demographic Health Survey (DHS) released the first data about child labour in Egypt in 2014. This study builds on the few findings of earlier work, and broadens coverage by including advanced methods and geographical effects of this problem. Objectives This study focuses on identifying socio-demographic, economic and geospatial factors associated with child labour participation. Methods We used the 2014 Egypt Demographic and Health Survey (EDHS) from the Ministry of Health and Population in Egypt, with the record of 20,560 never-married children aged 5–17 years engaging in economic activities, in and out of their home. The data focused on demographic and socio-economic characteristics of household members. Multivariate Bayesian geo-additive models were employed to examine the demographical and socio-economic factors for children working less than 16 hrs; between 16 and less 45 hrs; and over 45 hrs weekly. Results The results showed that at least 31.6% of the children in the age group from 5–10 were working, 68.5% of children aged 11–17 years were engaged in child labour for a wage, and 44.7% of the children in the age group from 5–10 were engaged in hazardous work. From the multivariate Bayesian geo-additive models, female children (with male children as reference category) working at least 16 hrs (OR: 1.3; with 95% CI: 1.2–1.5) were more likely to be engaged in child labour than girls working 16 to 45 hrs (OR: 1; 95% CI: 0.3–1.5). Children born to women without formal education, in non-hazardous jobs, irrespective of the hours spent at work, were more likely to be involved in child labour (52.9%, 56.8%, 62.4%) compared to children of mothers with some level of education. Finally, children who have experienced psychological aggression and physical punishment are more likely to be used as child labour than those without such experience across the job types and hours spent. North-eastern Egypt has a higher likelihood of child labour than most other regions, while children who live in the Delta are more engaged in hazardous work. Conclusion This study revealed a significant influence of socio-demographic and economic factors on child labour and violence against children in Egypt. Poverty, neglect, lack of adequate care and exposure of children to various grades of violence are major drivers of child labour across the country. The spatial effect suggests the need to give more attention to some areas that have high rates of child labour, such as the Nile Delta, Upper Egypt, and North-eastern Egypt

Discontinuation of cART postpartum in a high prevalence district of South Africa in 2014

BACKGROUND: Combination antiretroviral therapy (cART) is the current strategy to prevent mother-to-child transmission (PMTCT) of HIV. Women initiated on cART should continue taking treatment life-long or stop after cessation of breastfeeding depending on their CD4 cell count or on their World Health Organization (WHO) staging. Keeping people living with HIV on treatment is essential for the success of any antiretroviral therapy (ART) programme. There has been a rapid scale-up of cART in the PMTCT programme in South Africa. cART is supposed to be taken life-long or until cessation of breastfeeding, but premature or unmanaged discontinuation of cART postpartum is not unusual in South Africa and is confirmed by studies from around the world. Discontinuation of cART can lead to mother-to-child transmission (MTCT), drug resistance and poor maternal outcomes. The extent of this problem in the South African context however is unclear. This study aims to determine the prevalence of and identify risk factors associated with discontinuation of cART postpartum amongst women who were initiated on antiretroviral treatment during their index pregnancy. METHODS: An observational analytic cross-sectional study design will be conducted in six health facilities in a high prevalence district in KwaZulu-Natal, South Africa over a period of 3 months in 2014. An interviewer-administered questionnaire will be used to collect data from mothers who initiated cART during their index pregnancy. The prevalence of discontinuation of cART postpartum will be measured, and the association between those who discontinue cART postpartum and independent variables will be estimated using multivariable-adjusted prevalence odds ratios for discontinuation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-014-0139-3) contains supplementary material, which is available to authorized users

Subnational mapping of HIV incidence and mortality among individuals aged 15-49 years in sub-Saharan Africa, 2000-18: a modelling study

Background High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8–8120·3]) cases per 100 000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0–1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81·1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. Interpretation Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas. Funding Bill & Melinda Gates Foundation

Capturing the spatial variability of HIV epidemics in South Africa and Tanzania using routine healthcare facility data

Background: Large geographical variations in the intensity of the HIV epidemic in sub-Saharan Africa call for geographically targeted resource allocation where burdens are greatest. However, data available for mapping the geographic variability of HIV prevalence and detecting HIV ‘hotspots’ is scarce, and population-based surveillance data are not always available. Here, we evaluated the viability of using clinic-based HIV prevalence data to measure the spatial variability of HIV in South Africa and Tanzania. Methods: Population-based and clinic-based HIV data from a small HIV hyper-endemic rural community in South Africa as well as for the country of Tanzania were used to map smoothed HIV prevalence using kernel interpolation techniques. Spatial variables were included in clinic-based models using co-kriging methods to assess whether cofactors improve clinic-based spatial HIV prevalence predictions. Clinic- and population-based smoothed prevalence maps were compared using partial rank correlation coefficients and residual local indicators of spatial autocorrelation. Results: Routinely-collected clinic-based data captured most of the geographical heterogeneity described by population-based data but failed to detect some pockets of high prevalence. Analyses indicated that clinic-based data could accurately predict the spatial location of so-called HIV ‘hotspots’ in &gt; 50% of the high HIV burden areas. Conclusion: Clinic-based data can be used to accurately map the broad spatial structure of HIV prevalence and to identify most of the areas where the burden of the infection is concentrated (HIV ‘hotspots’). Where population-based data are not available, HIV data collected from health facilities may provide a second-best option to generate valid spatial prevalence estimates for geographical targeting and resource allocation

Topographic mapping of the interfaces between human and aquatic mosquito habitats to enable barrier targeting of interventions against malaria vectors.

Geophysical topographic metrics of local water accumulation potential are freely available and have long been known as high-resolution predictors of where aquatic habitats for immature mosquitoes are most abundant, resulting in elevated densities of adult malaria vectors and human infection burden. Using existing entomological and epidemiological survey data, here we illustrate how topography can also be used to map out the interfaces between wet, unoccupied valleys and dry, densely populated uplands, where malaria vector densities and infection risk are focally exacerbated. These topographically identifiable geophysical boundaries experience disproportionately high vector densities and malaria transmission risk, because this is where mosquitoes first encounter humans when they search for blood after emerging or ovipositing in the valleys. Geophysical topographic indicators accounted for 67% of variance for vector density but for only 43% for infection prevalence, so they could enable very selective targeting of interventions against the former but not the latter (targeting ratios of 5.7 versus 1.5 to 1, respectively). So, in addition to being useful for targeting larval source management to wet valleys, geophysical topographic indicators may also be used to selectively target adult mosquitoes with insecticidal residual sprays, fencing, vapour emanators or space sprays to barrier areas along their fringes

How much incident lung cancer was missed globally in 2012? An ecological country-level study

Lung cancer incidence is increasing in many low-to-middle-income countries and is significantly under-reported in Africa, which could potentially mislead policy makers when prioritising disease burden. We employed an ecological correlation study design using countrylevel lung cancer incidence data and associated determinant data. Lagged prevalence of smoking and other exposure data were used to account for exposure-disease latency. A multivariable Poisson model was employed to estimate missed lung cancer in countries lacking incidence data. Projections were further refined to remove potential deaths from infectious/external competing causes. Global lung cancer incidence was much lower among females vs males (13.6 vs 34.2 per 100,000). Distinct spatial heterogeneity was observed for incident lung cancer and appeared concentrated in contiguous regions. Our model predicted a revised global lung cancer incidence in 2012 of 23.6 compared to the Globocan 2012 estimate of 23.1, amounting to ~38,101 missed cases (95% confidence interval: 28,489-47,713). The largest relative under-estimation was predicted for Africa, Central America and the Indian Ocean regions (Comoros, Madagascar, Mauritius, Mayotte, Reunion, Seychelles). Our results suggest substantial underreporting of lung cancer incidence, specifically in developing countries (e.g. Africa). The missed cost of treating these cases could amount to &gt;US$ 130 million based on recent developing setting costs for treating earlier stage lung cancer. The full cost is not only under-estimated, but also requires substantial additional social/family inputs as evidenced in more developed settings like the European Union. This represents a major public health problem in developing settings (e.g. Africa) with limited healthcare resources

Prevalence of metabolic syndrome, discrete or comorbid diabetes and hypertension in sub-Saharan Africa among people living with HIV versus HIV-negative populations : a systematic review and meta-analysis protocol

INTRODUCTION: Metabolic disorder and high blood pressure are common complications globally, and specifically among people living with HIV (PLHIV). Diabetes, metabolic syndrome and hypertension are major risk factors for cardiovascular diseases and their related complications. However, the burden of metabolic syndrome, discrete or comorbid diabetes and hypertension in PLHIV compared with HIV-negative population has not been quantified. This review and meta-analysis aims to compare and analyse the prevalence of these trio conditions between HIV-negative and HIV-positive populations in sub-Saharan Africa (SSA). METHODS AND ANALYSIS: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement guides the methods for this study. Eligibility criteria will be published original articles (English and French language) from SSA that present the prevalence of metabolic syndrome, discrete and/or comorbid diabetes, and hypertension comparisons between PLHIV and HIV-negative populations. The following databases will be searched from January 1990 to February 2017: PubMed/Medline, EBSCOhost, Web of Science, Google Scholar, Scopus, African Index Medicus and Cochrane Database of Systematic Reviews. Eligibility screening and data extraction will be conducted independently by two reviewers, and disagreements resolved by an independent reviewer. Methodological quality and risk of bias will be assessed for individual included studies, while meta-analysis will be used to estimate study outcomes prevalence according to subgroups. Sensitivity analysis will also be performed to further test the robustness of the findings. ETHICS AND DISSEMINATION: This proposed study does not require ethical approval. The results will be published as a scientific article in a peer-reviewed journal, and presented at conferences and to relevant health agencies. TRIAL REGISTRATION NUMBER: PROSPERO registration number (CRD42016045727)

Joint spatio-temporal modelling of adverse pregnancy outcomes sharing common risk factors at sub-county level in Kenya, 2016–2019

Background Adverse pregnancy outcomes jointly account for a high proportion of mortality and morbidity among pregnant women and their infants. Furthermore, the burden attributed to adverse pregnancy outcomes remains high and inadequately characterised due to the intricate interplay of its etiology and shared set of important risk factors. This study sought to quantify and map the underlying risk of multiple adverse pregnancy outcomes in Kenya at sub-county level using a shared component space-time modelling framework. Methods Reported sub-county level adverse pregnancy outcomes count from January 2016 – December 2019 were obtained from the Kenyan District Health Information System. A Bayesian hierarchical spatio-temporal model was used to estimate the joint burden of adverse pregnancy outcomes in space (sub-county) and time (year). To improve the precision of our estimates over time and space, information across the outcomes were combined via the shared and the outcome-specific components using a shared component model with spatio-temporal interactions. Results Overall, the total number of adverse outcomes in pregnancy increased by 14.2% (95% UI: 14.0–14.5) from 88,816 cases in 2016 to 101,455 cases in 2019. Between 2016 and 2019, the estimated low birth weight rate and the pre-term birth rate were 4.5 (95% UI: 4.4–4.7) and 2.3 (95% UI: 2.2–2.5) per 100 live births. The stillbirth and neonatal death rates were estimated to be 18.7 (95% UI: 18.0–19.4) and 6.9 (95% UI: 6.4–7.4) per 1000 live births. The magnitude of the spatio-temporal variation attributed to shared risk was high for pre-term births, low birth weight, neonatal deaths, stillbirths and neonatal deaths, respectively. The shared risk patterns were dominant in sub-counties located along the Indian ocean coastline, central and western Kenya. Conclusions This study demonstrates the usefulness of a Bayesian joint spatio-temporal shared component model in exploiting specific and shared risk of adverse pregnancy outcomes sub-nationally. By identifying sub-counties with elevated risks and data gaps, our estimates not only assert the need for bolstering maternal health programs in the identified high-risk sub-counties but also provides a baseline against which to assess the progress towards the attainment of Sustainable Development Goals

Who dies where, when and why? Modelling determinants and space-time risk of infant, child and adult mortality in rural South Africa, 1992-2008

Ph.D., University of the Witwatersrand, Faculty of Health Sciences, 201