In 2005, the measles virus killed 345,000 people, mostly all of who were children. Due to low overall vaccine coverage, children living in Africa and South Asia have the greatest risk of measles morbidity and mortality. Recent data show that the West African nation of Niger has one of the highest rates of measles incidence per capita in the world. Niger is particularly unusual because of its cultural diversity and extreme environmental variation. The vast majority of Nigerien employment is agriculturally related. This means that the annual rainy season dictates land use, agricultural production, and labor. Alternating annual rainy and dry seasons result in dynamic land use patterns and host mixing. Seasonal patterns in host aggregation and transmission have been shown to force the timing of measles epidemics. The data from Niger consistently show that measles outbreaks occur only in the dry season, suggesting an increase in contact rates during the epidemics. The data also show asynchronous epidemics within the country, indicating low contact rates between these areas.
Results/Conclusions
We focus on understanding realistic social structures and movements by recognizing dynamic social contacts in a highly mobile and culturally diverse host population. High host movement levels across regions with high measles incidence emphasize the consideration of dynamic population sizes in disease analyses. Based on our hypothesis that host movements in Niger occur towards agriculturally usable land during the rainy season, we use geospatial measurements to calculate the amount of usable land area as it changes throughout the year to estimate host movement. These indices provide measures for estimating the changes in population density and number of contacts, the drivers of measles dynamics and spatiotemporal spread in Niger. We use this information to show how variations in seasonal drivers across the country of Niger impact the transmission of measles. Our results explain the unpredictable effects of a very strong seasonal driver on a highly infectious disease and refine our understanding of the spatiotemporal dynamics of this important infection.
