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LaBeaud, A. D.

Publications and source records attributed to LaBeaud, A. D..

2 recordsLinked to original sources

Climate explains geographic and temporal variation in mosquito-borne disease dynamics on two continents

Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28 - 85% for vectors, 44 - 88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.

ecology↗

Making Pastoralists Count: Geospatial Methods for the Health Surveillance of Nomadic Populations

Nomadic pastoralists are among the worlds hardest-to-reach and least-served populations. Pastoralist communities are difficult to capture in household surveys due to factors including their high degree of mobility over remote terrain, fluid domestic arrangements, and cultural barriers. Most surveys utilize census-based sampling frames which do not accurately capture the demographic and health parameters of nomadic populations. As a result, pastoralists are \"invisible\" in population data such as the Demographic and Health Surveys (DHS). By combining remote sensing and geospatial analysis, we developed a sampling strategy designed to capture the current distribution of nomadic populations.\n\nWe then implemented this sampling frame to survey a population of mobile pastoralists in southwest Ethiopia, focusing on maternal and child health (MCH) indicators. Using standardized instruments from DHS questionnaires, we draw comparisons with regional and national data finding disparities with DHS data in core MCH indicators including vaccination coverage, skilled birth attendance, and nutritional status. Our field validation demonstrates that this method is a logistically feasible alternative to conventional sampling frames and may be used at the population level. Geospatial sampling methods provide cost-affordable and logistically feasible strategies for sampling mobile populations, a crucial first step towards reaching these groups with health services.

epidemiology↗