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CURATOR
A pinboard by
Rachel Sippy

Graduate trainee, University of Wisconsin-Madison

PINBOARD SUMMARY

Climate drivers of annual dengue epidemics in Ecuador

Season is a major determinant of infectious disease rates, including mosquito-borne arboviruses, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climate factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of mosquito-borne illnesses has been studied in the context of climate, but temporal trends are less well-understood. With 2009—2016 medical record data from patients diagnosed with arboviral illness at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of mosquito-borne disease, and the effect of climate factors. The most important predictors of illness were annual fluctuations in disease, long-term trends, day of the week, and climate variables. Compared to Tuesday, weekends were the least likely days for arboviral illness to be diagnosed, with 34% (p=0.007) and 40% (p=0.001) less cases reported on Saturday and Sunday, respectively. Seasonal trends showed a single peak during April, with long-term trends showing an overall decrease in diagnoses and suggested inter-epidemic periods every two or three years. Important climate variables included total monthly precipitation (p=0.002), Oceanic Niño Index (p=0.039), interactions between total precipitation and monthly absolute minimum temperature (p=0.002), total precipitation and monthly number of days with precipitation (p=0.019), and three-way interaction between minimum temperature, total precipitation, and precipitation days (p=0.014). Seasonality assessments revealed 10- to 30-day lags between peaks in climate variables and disease. This is the first report of arboviral disease seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, and global or regional models of arboviral disease trends.

4 ITEMS PINNED

Estimating dengue vector abundance in the wet and dry season: implications for targeted vector control in urban and peri-urban Asia.

Abstract: Research has shown that the classical Stegomyia indices (or "larval indices") of the dengue vector Aedes aegypti reflect the absence or presence of the vector but do not provide accurate measures of adult mosquito density. In contrast, pupal indices as collected in pupal productivity surveys are a much better proxy indicator for adult vector abundance. However, it is unknown when it is most optimal to conduct pupal productivity surveys, in the wet or in the dry season or in both, to inform control services about the most productive water container types and if this pattern varies among different ecological settings.A multi-country study in randomly selected twelve to twenty urban and peri-urban neighborhoods ("clusters") of six Asian countries, in which all water holding containers were examined for larvae and pupae of Aedes aegypti during the dry season and the wet season and their productivity was characterized by water container types. In addition, meteorological data and information on reported dengue cases were collected.The study reconfirmed the association between rainfall and dengue cases ("dengue season") and underlined the importance of determining through pupal productivity surveys the "most productive containers types", responsible for the majority (>70%) of adult dengue vectors. The variety of productive container types was greater during the wet than during the dry season, but included practically all container types productive in the dry season. Container types producing pupae were usually different from those infested by larvae indicating that containers with larval infestations do not necessarily foster pupal development and thus the production of adult Aedes mosquitoes.Pupal productivity surveys conducted during the wet season will identify almost all of the most productive container types for both the dry and wet seasons and will therefore facilitate cost-effective targeted interventions.

Pub.: 16 Jan '13, Pinned: 17 Jun '17

Dengue diversity across spatial and temporal scales: Local structure and the effect of host population size.

Abstract: A fundamental mystery for dengue and other infectious pathogens is how observed patterns of cases relate to actual chains of individual transmission events. These pathways are intimately tied to the mechanisms by which strains interact and compete across spatial scales. Phylogeographic methods have been used to characterize pathogen dispersal at global and regional scales but have yielded few insights into the local spatiotemporal structure of endemic transmission. Using geolocated genotype (800 cases) and serotype (17,291 cases) data, we show that in Bangkok, Thailand, 60% of dengue cases living <200 meters apart come from the same transmission chain, as opposed to 3% of cases separated by 1 to 5 kilometers. At distances <200 meters from a case (encompassing an average of 1300 people in Bangkok), the effective number of chains is 1.7. This number rises by a factor of 7 for each 10-fold increase in the population of the "enclosed" region. This trend is observed regardless of whether population density or area increases, though increases in density over 7000 people per square kilometer do not lead to additional chains. Within Thailand these chains quickly mix, and by the next dengue season viral lineages are no longer highly spatially structured within the country. In contrast, viral flow to neighboring countries is limited. These findings are consistent with local, density-dependent transmission and implicate densely populated communities as key sources of viral diversity, with home location the focal point of transmission. These findings have important implications for targeted vector control and active surveillance.

Pub.: 25 Mar '17, Pinned: 17 Jun '17