Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning

Objective: There is evidence of substantial subnational variation in the HIV epidemic. However, robust spatial HIV data are often only available at high levels of geographic aggregation and not at the finer resolution needed for decision making. Therefore, spatial analysis methods that leverage available data to provide local estimates of HIV prevalence may be useful. Such methods exist but have not been formally compared when applied to HIV. Design/methods: Six candidate methods – including those used by the Joint United Nations Programme on HIV/AIDS to generate maps and a Bayesian geostatistical approach applied to other diseases – were used to generate maps and subnational estimates of HIV prevalence across three countries using cluster level data from household surveys. Two approaches were used to assess the accuracy of predictions: internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions; and comparison with location-specific data from household surveys in earlier years. Results: Each of the methods can generate usefully accurate predictions of prevalence at unsampled locations, with the magnitude of the error in predictions similar across approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures. Conclusions: Available methods may be able to furnish estimates of HIV prevalence at finer spatial scales than the data currently allow. The subnational variation revealed can be integrated into planning to ensure responsiveness to the spatial features of the epidemic. The Bayesian geostatistical approach is a promising strategy for integrating HIV data to generate robust local estimates

Reproductive health services for populations at high risk of HIV: Performance of a night clinic in Tete province, Mozambique

<p>Abstract</p> <p>Background</p> <p>Different models exist to provide HIV/STI services for most-at-risk populations (MARP). Along the Tete traffic corridor in Mozambique, linking Malawi and Zimbabwe, a night clinic opening between 4 and 10 PM was established targeting female sex workers (FSW) and long-distance truck drivers (LDD). The clinic offers free individual education and counselling, condoms, STI care, HIV testing, contraceptive services and outreach peer education. To evaluate this clinic model, we assessed relevance, service utilisation, efficiency and sustainability.</p> <p>Methods</p> <p>In 2007-2009, mapping and enumeration of FSW and LDD was conducted; 28 key informants were interviewed; 6 focus group discussions (FGD) were held with FSW from Mozambique and Zimbabwe, and LDD from Mozambique and Malawi. Clinic outputs and costs were analysed.</p> <p>Results</p> <p>An estimated 4,415 FSW work in the area, or 9% of women aged 15-49, and on average 66 trucks stay overnight near the clinic. Currently on average, 475 clients/month visit the clinic (43% for contraception, 24% for counselling and testing and 23% for STI care). The average clinic running cost is US$ 1408/month, mostly for human resources. All informants endorsed this clinic concept and the need to expand the services. FGD participants reported high satisfaction with the services and mentioned good reception by the health staff, short waiting times, proximity and free services as most important. Participants were in favour of expanding the range of services, the geographical coverage and the opening times.</p> <p>Conclusions</p> <p>Size of the target population, satisfaction of clients and endorsement by health policy makers justify maintaining a separate clinic for MARP. Cost-effectiveness may be enhanced by broadening the range of SRHR-HIV/AIDS services, adapting opening times, expanding geographical coverage and targeting additional MARP. Long-term sustainability remains challenging and requires private-public partnerships or continued project-based funding.</p

Instability, investment, disasters, and demography: natural disasters and fertility in Italy (1820–1962) and Japan (1671–1965)

This article examines whether natural disasters affect fertility—a topic little explored but of policy importance given relevance to policies regarding disaster insurance, foreign aid, and the environment. The identification strategy uses historic regional data to exploit natural variation within each of two countries: one European country—Italy (1820–1962), and one Asian country—Japan (1671–1965). The choice of study settings allows consideration of Jones’ (The European miracle, Cambridge University Press, Cambridge, 1981) theory that preindustrial differences in income and population between Asia and Europe resulted from the fertility response to different environmental risk profiles. According to the results, short-run instability, particularly that arising from the natural environment, appears to be associated with a decrease in fertility—thereby suggesting that environmental shocks and economic volatility are associated with a decrease in investment in the population size of future generations. The results also show that, contrary to Jones’ (The European miracle, Cambridge University Press, Cambridge, 1981) theory, differences in fertility between Italy and Japan cannot be explained away by disaster proneness alone. Research on the effects of natural disasters may enable social scientists and environmentalists alike to better predict the potential effects of the increase in natural disasters that may result from global climate change

Modelling the impact of women’s education on fertility in Malawi

Many studies have suggested that there is an inverse relationship between education and number of children among women from sub-Saharan Africa countries, including Malawi. However, a crucial limitation of these analyses is that they do not control for the potential endogeneity of education. The aim of our study is to estimate the role of women’s education on their number of children in Malawi, accounting for the possible presence of endogeneity and for nonlinear effects of continuous observed confounders. Our analysis is based on micro data from the 2010 Malawi Demographic Health Survey, and uses a flexible instrumental variable regression approach. The results suggest that the relationship of interest is affected by endogeneity and exhibits an inverted U-shape among women living in rural areas of Malawi, whereas it exhibits an inverse (nonlinear) relationship for women living in urban areas

Regional inequalities in under-5 mortality in Nigeria: a population-based analysis of individual- and community-level determinants

<p>Abstract</p> <p>Background</p> <p>Regions with geographically diverse ecology and socioeconomic circumstances may have different disease exposures and child health outcomes. This study assessed variations in the risks of death in children under age 5 across regions of Nigeria and determined characteristics at the individual and community levels that explain possible variations among regions.</p> <p>Methods</p> <p>Multilevel Cox proportional hazards analysis was performed using a nationally representative sample of 6,029 children from 2,735 mothers aged 15-49 years and nested within 365 communities from the 2003 Nigeria Demographic and Health Survey. Hazard ratios (HR) with 95% confidence intervals (CI) were used to express measures of association among the characteristics. Variance partition coefficients and Wald statistic were used to express measures of variation.</p> <p>Results</p> <p>Patterns of under-5 mortality cluster within families and communities. The risks of under-5 deaths were significantly higher for children of mothers residing in the South South (Niger Delta) region (HR: 1.30; 95% CI: 1.76-2.20) and children of mothers residing in communities with a low proportion of mothers attending prenatal care by a doctor (HR: 1.36; 95% CI: 1.15-1.86). In addition, the cross-level interaction between mothers' education and community prenatal care by a doctor was associated with a more than 40% higher risk of dying (HR: 1.41; 95% CI: 1.21-1.78).</p> <p>Conclusion</p> <p>The findings suggest the need to differentially focus on community-level interventions aimed at increasing maternal and child health care utilization and improving the socioeconomic position of mothers, especially in disadvantaged regions such as the South South (Niger Delta) region. Further studies on community-levels determinants of under-5 mortality are needed.</p

The effects of spatial population dataset choice on estimates of population at risk of disease

Background: The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.Methods: The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets.Results: The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets.Conclusions: Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. © 2011 Tatem et al; licensee BioMed Central Ltd.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Sociocultural and epidemiological aspects of HIV/AIDS in Mozambique

<p>Abstract</p> <p>Background</p> <p>A legacy of colonial rule coupled with a devastating 16-year civil war through 1992 left Mozambique economically impoverished just as the human immunodeficiency virus (HIV) epidemic swept over southern Africa in the late 1980s. The crumbling Mozambican health care system was wholly inadequate to support the need for new chronic disease services for people with the acquired immunodeficiency syndrome (AIDS).</p> <p>Methods</p> <p>To review the unique challenges faced by Mozambique as they have attempted to stem the HIV epidemic, we undertook a systematic literature review through multiple search engines (PubMed, Google Scholar™, SSRN, AnthropologyPlus, AnthroSource) using Mozambique as a required keyword. We searched for any articles that included the required keyword as well as the terms 'HIV' and/or 'AIDS', 'prevalence', 'behaviors', 'knowledge', 'attitudes', 'perceptions', 'prevention', 'gender', drugs, alcohol, and/or 'health care infrastructure'.</p> <p>Results</p> <p>UNAIDS 2008 prevalence estimates ranked Mozambique as the 8^thmost HIV-afflicted nation globally. In 2007, measured HIV prevalence in 36 antenatal clinic sites ranged from 3% to 35%; the national estimate of was 16%. Evidence suggests that the Mozambican HIV epidemic is characterized by a preponderance of heterosexual infections, among the world's most severe health worker shortages, relatively poor knowledge of HIV/AIDS in the general population, and lagging access to HIV preventive and therapeutic services compared to counterpart nations in southern Africa. Poor education systems, high levels of poverty and gender inequality further exacerbate HIV incidence.</p> <p>Conclusions</p> <p>Recommendations to reduce HIV incidence and AIDS mortality rates in Mozambique include: health system strengthening, rural outreach to increase testing and linkage to care, education about risk reduction and drug adherence, and partnerships with traditional healers and midwives to effect a lessening of stigma.</p

Determinants of Infant Mortality in Older ASEAN Economies

Infant mortality in the Association of Southeast Asian Nations (ASEAN) has been declining, yet disparities remain between the nations. This paper therefore explores the determinants of infant mortality in the older ASEAN-4 economies, Malaysia, Thailand, Indonesia and the Philippines using an Autoregressive Distributed Lag (ARDL) Error Correction Model framework. The key findings of the study are: First, there is evidence of long-run relationships among infant mortality, education, female fertility, income and access to healthcare. Second, the determinants of infant mortality vary between countries. Female fertility emerged as the main determinant of infant mortality in Malaysia, while access to healthcare matter for infant mortality in Indonesia, and to a lesser extent for the Philippines. The income effect is significant for reducing infant mortality in Malaysia, while female education is important for Indonesia and Thailand. Third, the speed of adjustment of infant mortality rate is comparatively low in ASEAN-4