A Malaria Ecology Index Predicted Spatial and Temporal Variation of Malaria Burden and Efficacy of Antimalarial Interventions Based on African Serological Data.

Reducing the global health burden of malaria is complicated by weak reporting systems for infectious diseases and a paucity of vital statistics registration. This limits our ability to predict changes in malaria health burden intensity, target antimalarial resources where needed, and identify malaria impacts in retrospective data. We refined and deployed a temporally and spatially varying Malaria Ecology Index (MEI) incorporating climatological and ecological data to estimate malaria transmission strength and validate it against cross-sectional serology data from 39,875 children from seven sub-Saharan African countries. The MEI is strongly associated with malaria burden; a 1 standard deviation higher MEI is associated with a 50-117% increase in malaria risk and a 3-5 g/dL lower level of Hg. Results show that the relationship between malaria ecology and disease burden is attenuated with sufficient coverage of insecticide treated nets (ITNs) or indoor residual spraying (IRS). Having both ITNs and IRS reduce the added risk from adverse malaria ecology conditions by half. Readily available climate and ecology data can be used to estimate the spatial and temporal variation in malaria disease burden, providing a feasible alternative to direct surveillance. This will help target resources for malaria programs in the absence of national coverage of active case detection systems, and facilitate malaria research using retrospective health data

Can Social Protection Reduce Environmental Damages?

Why do damages from changes in environmental quality differ across and within countries? Causal investigation of this question has been challenging because differences may stem from heterogeneity in cumulative exposure or differences in socioeconomic factors such as income. We revisit the temperature-violence relationship and show that cash transfers attenuate one-half to two-thirds of the effects of higher same-day temperatures on homicides. Our results not only demonstrate causally that income can explain much of the heterogeneity in the marginal effects of higher temperatures, but also imply that social protection programs can help the poor adapt to rising temperatures

Malaria ecology, child mortality & fertility.

The broad determinants of fertility are thought to be reasonably well identified by demographers, though the detailed quantitative drivers of fertility levels and changes are less well understood. This paper uses a novel ecological index of malaria transmission to study the effect of child mortality on fertility. We find that temporal variation in the ecology of the disease is well-correlated to mortality, and pernicious malaria conditions lead to higher fertility rates. We then argue that most of this effect occurs through child mortality, and estimate the effect of child mortality changes on fertility. Our findings add to the literature on disease and fertility, and contribute to the suggestive evidence that child mortality reductions have a causal effect on fertility changes

Scaling Up Malaria Control in Africa: An Economic and Epidemiological Assessment

This paper estimates the number of people at risk of contracting malaria in Africa using GIS methods and the disease's epidemiologic characteristics. It then estimates yearly costs of covering the population at risk with the package of interventions (differing by level of malaria endemicity and differing for rural and urban populations) for malaria as recommended by the UN Millennium Project. These projected costs are calculated assuming a ramp-up of coverage to full coverage by 2008, and then projected out through 2015 to give a year-by-year cost of meeting the Millennium Development Goal for reducing the burden of malaria by 75% We conclude that the cost of comprehensive malaria control for Africa is US$3.0 billion per year on average, or around US$4.02 per African at risk.

Africa's Lagging Demographic Transition: Evidence from Exogenous Impacts of Malaria Ecology and Agricultural Technology

Much of Africa has not yet gone through a "demographic transition" to reduced mortality and fertility rates. The fact that the continent's countries remain mired in a Malthusian crisis of high mortality, high fertility, and rapid population growth (with an accompanying state of chronic extreme poverty) has been attributed to many factors ranging from the status of women, pro-natalist policies, poverty itself, and social institutions. There remains, however, a large degree of uncertainty among demographers as to the relative importance of these factors on a comparative or historical basis. Moreover, econometric estimation is complicated by endogeneity among fertility and other variables of interest. We attempt to improve estimation (particularly of the effect of the child mortality variable) by deploying exogenous variation in the ecology of malaria transmission and in agricultural productivity through the staggered introduction of Green Revolution, high-yield seed varieties. Results show that child mortality (proxied by infant mortality) is by far the most important factor among those explaining aggregate total fertility rates, followed by farm productivity. Female literacy (or schooling) and aggregate income do not seem to matter as much, comparatively.

What Can We Learn from Nighttime Lights for Small Geographies? Measurement Errors and Heterogeneous Elasticities

Nighttime lights are routinely used as a proxy for economic activity when official statistics are unavailable and are increasingly applied to study the effects of shocks or policy interventions at small geographic scales. The implicit assumption is that the ability of nighttime lights to pick up changes in GDP does not depend on local characteristics of the region under investigation or the scale of aggregation. This study uses panel data on regional GDP growth from six countries, and nighttime lights from the Defense Meteorological Satellite Program (DMSP) to investigate potential nonlinearities and measurement errors in the light production function. Our results for high statistical capacity countries (the United States and Germany) show that nightlights are significantly less responsive to changes in GDP at higher baseline level of GDP, higher population densities, and for agricultural GDP. We provide evidence that these nonlinearities are too large to be caused by differences in measurement errors across regions. We find similar but noisier relationships in other high-income countries (Italy and Spain) and emerging economies (Brazil and China). We also present results for different aggregation schemes and find that the overall relationship, including the nonlinearity, is stable across regions of different shapes and sizes but becomes noisier when regions become few and large. These findings have important implications for studies using nighttime lights to evaluate the economic effects of shocks or policy interventions. On average, nighttime lights pick up changes in GDP across many different levels of aggregation, down to relatively small geographies. However, the nonlinearity we document in this paper implies that some studies may fail to detect policy-relevant effects in places where lights react little to changes in economic activity or they may mistakenly attribute this heterogeneity to the treatment effect of their independent variable of interest

Africa's Lagging Demographic Transition: Evidence from Exogenous Impacts of Malaria Ecology and Agricultural Technology

Much of Africa has not yet gone through a "demographic transition" to reduced mortality and fertility rates. The fact that the continent's countries remain mired in a Malthusian crisis of high mortality, high fertility, and rapid population growth (with an accompanying state of chronic extreme poverty) has been attributed to many factors ranging from the status of women, pro-natalist policies, poverty itself, and social institutions. There remains, however, a large degree of uncertainty among demographers as to the relative importance of these factors on a comparative or historical basis. Moreover, econometric estimation is complicated by endogeneity among fertility and other variables of interest. We attempt to improve estimation (particularly of the effect of the child mortality variable) by deploying exogenous variation in the ecology of malaria transmission and in agricultural productivity through the staggered introduction of Green Revolution, high-yield seed varieties. Results show that child mortality (proxied by infant mortality) is by far the most important factor among those explaining aggregate total fertility rates, followed by farm productivity. Female literacy (or schooling) and aggregate income do not seem to matter as much, comparatively

Essays on Malaria, Environment and Society

The body of work presented here seeks to illuminate the complex relationship between human society, development, and environment for the case of malaria. While malaria profoundly affects human society and prospects for prosperity, public health measures and anthropogenic environmental change alter the intensity of transmission differentially around the globe. Using global maps of malaria risk, the first chapter finds that the elimination of the disease during the course of the 20th century occurred in places where the strength of transmission was weaker due to suboptimal ecology, and that this result holds even after controlling for income levels. The next chapter employs GIS datasets on population, urbanization, malaria risk, and malaria endemicity to spatially estimate the cost of fully deploying ecology-appropriate anti-malaria interventions in Africa; the cost of curbing malaria is found to be small (around $4 per person at risk per year), especially given its high disease burden and subsequent social and economic costs. I next construct a spatial month-to-month ecological index of malaria transmission strength, and use a climate change model to predict changes in ecological transmission strength of malaria and estimate the implied changes in incidence and mortality given current technology and public health efforts. The final chapter uses the malaria ecology index as an instrumental variable to estimate the effect of child mortality on fertility behavior. The large effect of child mortality indicates that malaria has an indirect effect on society beyond morbidity and mortality: high malaria burdens increase fertility rates, thus slowing the demographic transition. These chapters span the fields of epidemiology, public health systems, climate science, economics and demography in order to holistically model the relationship between malaria and human systems; such understanding of coupled human-natural systems will be vital to policy making for sustainable development

Ending Africa's Poverty Trap

macroeconomics, Africa, Poverty Trap, poverty

Prognostic Utility of a Modified HEART Score When Different Troponin Cut-points Are Used

BACKGROUND: Although the recommended cut-point for cardiac troponin (cTn) is the 99th percentile, many institutions use cut-points that are multiples higher than the 99th percentile for diagnosing acute myocardial infarction (AMI). Prior studies have shown that patients with a HEART score (HS) ≤ 3 and normal serial cTn values (modified HS) are at low risk for adverse events. This study aimed to evaluate the prognostic utility of the HS when various cTn cut-points are used. METHODS: This was a sub-study of TRAPID-AMI, a multicenter, international trial evaluating a rapid rule-out AMI study using high sensitivity cTnT (hs-cTnT). 1,282 patients were evaluated for AMI from 12 centers in Europe, United States of America, and Australia from 2011-2013. Blood samples of hs-cTnT were collected at presentation and 2 hours, and each patient had a HS calculated. The US Food and Drug Administration approved 99th percentile for hs-cTnT (19 ng/L) was used. RESULTS: There were 213 (17%) AMIs. Within 30 days, there were an additional 2 AMIs and 8 deaths. The adverse event rates at 30 days (death/AMI) for a HS ≤ 3 and non-elevated hs-cTnT over 2 hours using increasing hs-cTnT cut-points ranged from 0.6% to 5.1%. CONCLUSIONS: Using the recommended 99th percentile cut-point for hs-cTnT, the combination of a HS ≤ 3 with non-elevated hs-cTnT values over 2 hours identifies a low-risk cohort who can be considered for discharge from the emergency department without further testing. The prognostic utility of this strategy is greatly lessened as higher hs-cTnT cut-points are used