Dengue is the most important human arboviral disease in Singapore. We classified residential areas into low-rise and high-rise housing and investigated the influence of urban drainage on the distribution of dengue incidence and outdoor breeding at neighborhood and country scales. In Geylang area (August 2014 to August 2015), dengue incidence was higher in a subarea of low-rise housing compared to high-rise one, averaging 26.7 (standard error, SE = 4.83) versus 2.43 (SE = 0.67) per 1,000 people. Outdoor breeding drains of Aedes aegypti have clustered in the low-rise housing subarea. The pupal density per population was higher in the low-rise blocks versus high-rise ones, 246 (SE = 69.08) and 35.4 (SE = 25.49) per 1,000 people, respectively. The density of urban drainage network in the low-rise blocks is double that in the high-rise ones, averaging 0.05 (SE = 0.0032) versus 0.025 (SE = 0.00245) per meter. Further, a holistic analysis at a country-scale has confirmed the role of urban hydrology in shaping dengue distribution in Singapore. Dengue incidence (2013–2015) is proportional to the fractions of the area (or population) of low-rise housing. The drainage density in low-rise housing is 4 times that corresponding estimate in high-rise areas, 2.59 and 0.68 per meter, respectively. Public housing in agglomerations of high-rise buildings could have a positive impact on dengue if this urban planning comes at the expense of low-rise housing. City planners in endemic regions should consider the density of drainage networks for both the prevention of flooding and the breeding of mosquitoes.
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
New dam construction is known to exacerbate malaria transmission in Africa as the vectors of malaria—Anopheles mosquitoes—use bodies of water as breeding sites. Precise environmental mechanisms of how reservoirs exacerbate malaria transmission are yet to be identified. Understanding of these mechanisms should lead to a better assessment of the impacts of dam construction and to new prevention strategies. Combining extensive multi-year field surveys around the Koka Reservoir in Ethiopia and rigorous model development and simulation studies, environmental mechanisms of malaria transmission around the reservoir were examined. Most comprehensive and detailed malaria transmission model, HYDREMATS, was applied to a village adjacent to the reservoir. Significant contributions to the dynamics of malaria transmission are shaped by wind profile, marginal pools, temperature, and shoreline locations. Wind speed and wind direction influence Anopheles populations and malaria transmission during the major and secondary mosquito seasons. During the secondary mosquito season, a noticeable influence was also attributed to marginal pools. Temperature was found to play an important role, not so much in Anopheles population dynamics, but in malaria transmission dynamics. Change in shoreline locations drives malaria transmission dynamics, with closer shoreline locations to the village making malaria transmission more likely. Identified environmental mechanisms help in predicting malaria transmission seasons and in developing village relocation strategies upon dam construction to minimize the risk of malaria.
Invasive species rank second only to habitat destruction as a threat to native biodiversity. One consequence of biological invasions is altered risk of exposure to infectious diseases in human and animal populations. The distribution and prevalence of mosquito-borne diseases depend on the complex interactions between the vector, the pathogen, and the human or wildlife reservoir host. These interactions are highly susceptible to disturbance by invasive species, including terrestrial plants. We conducted a 2-year field experiment using a Before–After/Control–Impact design to examine how removal of invasive Amur honeysuckle (Lonicera maackii) in a forest fragment embedded within a residential neighborhood affects the abundance of mosquitoes, including two of the most important vectors of West Nile virus, Culex pipiens and Cx. restuans. We also assessed any potential changes in avian communities and local microclimate associated with Amur honeysuckle removal. We found that (1) removal of Amur honeysuckle reduces the abundance of both vector and non-vector mosquito species that commonly feed on human hosts, (2) the abundance and composition of avian hosts is altered by honeysuckle removal, and (3) areas invaded with honeysuckle support local microclimates that are favorable to mosquito survival. Collectively, our investigations demonstrate the role of a highly invasive understory shrub in determining the abundance and distribution of mosquitoes and suggest potential mechanisms underlying this pattern. Our results also give rise to additional questions regarding the general impact of invasive plants on vector-borne diseases and the spatial scale at which removal of invasive plants may be utilized to effect disease control.
Valley fever is endemic to the southwestern United States. Humans contract this fungal disease by inhaling spores of Coccidioides spp. Changes in the environment can influence the abundance and dispersal of Coccidioides spp., causing fluctuations in valley fever incidence. We combined county-level case records from state health agencies to create a regional valley fever database for the southwestern United States, including Arizona, California, Nevada, New Mexico, and Utah. We used this data set to explore how environmental factors influenced the spatial pattern and temporal dynamics of valley fever incidence during 2000–2015. We compiled climate and environmental geospatial data sets from multiple sources to compare with valley fever incidence. These variables included air temperature, precipitation, soil moisture, surface dust concentration, normalized difference vegetation index, and cropland area. We found that valley fever incidence was greater in areas with warmer air temperatures and drier soils. The mean annual cycle of incidence varied throughout the southwestern United States and peaked following periods of low precipitation and soil moisture. From year-to-year, however, autumn incidence was higher following cooler, wetter, and productive springs in the San Joaquin Valley of California. In southcentral Arizona, incidence increased significantly through time. By 2015, incidence in this region was more than double the rate in the San Joaquin Valley. Our analysis provides a framework for interpreting the influence of climate change on valley fever incidence dynamics. Our results may allow the U.S. Centers for Disease Control and Prevention to improve their estimates of the spatial pattern and intensity of valley fever endemicity.
Rotavirus is the most common cause of diarrheal disease among children under five. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of thirty-four (34) climate indices calculated from ground and satellite earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement (GPM) and temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors to validate the analyses and explore the potential of a satellite-based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks one to two-months in advance. The satellite data-driven forecasts also effectively captured the increased vulnerability of dry-cold regions of the country, compared to the wet-warm regions.