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Using data from a large, population based cohort in western Kenya, we first determine hotspot location, then quantify the spatial and temporal stability of malaria hotspots and identify both static and Aopen AOI-702R correlates of hotspot location. The main economic activities include sugarcane farming as a cash crop, while maize, sorghum and millet are cultivated as subsistence crops.

Dairy and poultry farming are also widely practiced. The area has a tropical climate and lies at an elevation of m above sea level. Malaria is perennial with peaks following the rains. Typically, transmission peaks in April-June following Aopen AOI-702R long rains with a smaller peak in October following the short rains. Baseline data collection occurred in November and continued for 4 months. Data collection was repeated biannually in the fall from September 1 to December 31 and in the spring from March 1 — June 30th. GPS coordinates were recorded for each compound, consisting of between 1—16 households. Households within a compound usually consist of extended family in separate but closely grouped dwellings.

Twice per year, enumerators visited every household to record all births, deaths, illnesses and migrations. Data were either collected on paper forms and entered into a database or collected on personal data Aopen AOI-702R using Pendragon forms. Due to inconsistencies in data collection in one survey round, one sublocation in the southernmost part of the study area was removed from the analysis.

Although teams moved from village to village within a sublocation, several teams of data collectors worked simultaneously in all parts of the WHDSS area at once during each round of data collection. Data processing Malaria Morbidity Information about all Aopen AOI-702R experienced by household members since the last study visit were self-reported in the case of minor children, reported by a guardian. Recall windows are therefore the amount of time elapsed since the previous study visit estimated median recall window is days.


Dates of illness and treatment were recorded. To avoid double-counting the same illness, any malaria episode that occurred within 3 weeks of an initial malaria illness was censored. To capture compound-level malaria incidence by season, malaria episodes were aggregated to the compound level and further aggregated by 6-month periods Spring: January-June; Fall: We required that an individual Aopen AOI-702R present within a compound for the entirety of the 6-month interval for their reported malaria episode to be counted for that compound. The recall period of morbidity data in the baseline round Round 1were not consistent with subsequent rounds, therefore, our analysis period begins with Round 2.

Globally, children age 0 to 5 are a high risk group for infection and morbidity due to malaria illness 22therefore, we performed all analyses on this subgroup in addition to the full census population.

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Definition of Hotspots Hotspots were defined spatially using the Kuldorff spatial-only scan statistic This approach to Aopen AOI-702R hotspots has been used in previous research 1467911 The scan statistic is calculated using a discrete Poisson model with an outcome of the count of malaria episodes per compound, per 6-month interval. Spatial scan test statistics are calculated by moving a circular window systematically through the study space of a geographic area and varying the radius of the window. A maximum likelihood ratio test evaluates whether the null or alternative model better fits the data at each location. The scan statistic is the maximum observed likelihood ratio statistic over all possible window sizes with a p-value obtained through Monte Carlo simulation based on discrete Poisson randomization.

P-values are adjusted to account for multiple testing across all potential clusters. The population at risk included all individuals present in a compound.

For analyses of the subpopulation of children age 0 to 5, we limited the population at risk to individuals in this Aopen AOI-702R group. By extension, only compounds that had at least one child in this age group during a particular round could be included in calculation of the scan statistic.

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Malaria reporting rates can vary over time due to the seasonality of transmission. Data collection rounds lasted for several months, therefore Aopen AOI-702R recall window for a household may fall within different parts of the malaria season from other households leading to differing recall lengths between households.

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To account for this, we performed covariate adjustment prior to computing spatial scan statistics by entering median village visit dates for a particular round into exponential models to compute predicted counts of malaria episodes at the compound level for each interval. Predicted values then replaced the population offsets to yield a visit date adjusted spatial scan statistic Scan statistics Aopen AOI-702R computed using spatial-only models and were repeated for every 6-month interval over the course of each of the five included study rounds. Relative risks of observed versus expected cases were computed for each identified cluster. Static Correlates with Febrile Hotspot Location We investigated compound socioeconomic characteristics plausibly correlated with the binary outcome of location within a hotspot.


In the WHDSS data, household socioeconomic variables are only available at enrollment, however we expect such characteristics to change little over time. Device: Aopen AOIR Description: Wireless LAN Version: R for Aopen AOI-702R / XP / / NT / ME Aopen AOIR driver for Windows / XP / Correct operation and full compatibility of your devices with the operating system require proper drivers to be installed. They are created by special technical.

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