The seasonality of cholera is described in various study areas throughout the world. However, no study examines how temporal cycles of the disease vary around the world or reviews its hypothesized causes. This paper reviews the literature on the seasonality of cholera and describes its temporal cycles by compiling and analyzing 32 years of global cholera data. This paper also provides a detailed literature review on regional patterns and environmental and climatic drivers of cholera patterns.

Background: The Department of Defense Military Health System operates a syndromic surveillance system that monitors medical records at more than 450 non-combat Military Treatment Facilities (MTF) worldwide. The Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE) uses both temporal and spatial algorithms to detect disease outbreaks. This study focuses on spatial detection and attempts to improve the effectiveness of the ESSENCE implementation of the spatial scan statistic by increasing the spatial resolution of incidence data from zip codes to street address level.Methods: Influenza-Like Illness (ILI) was used as a test syndrome to develop methods to improve the spatial accuracy of detected alerts. Simulated incident clusters of various sizes were superimposed on real ILI incidents from the 2008/2009 influenza season. Clusters were detected using the spatial scan statistic and their displacement from simulated loci was measured. Detected cluster size distributions were also evaluated for compliance with simulated cluster sizes.Results: Relative to the ESSENCE zip code based method, clusters detected using street level incidents were displaced on average 65% less for 2 and 5 mile radius clusters and 31% less for 10 mile radius clusters. Detected cluster size distributions for the street address method were quasi normal and sizes tended to slightly exceed simulated radii. ESSENCE methods yielded fragmented distributions and had high rates of zero radius and oversized clusters.Conclusions: Spatial detection accuracy improved notably with regard to both location and size when incidents were geocoded to street addresses rather than zip code centroids. Since street address geocoding success rates were only 73.5%, zip codes were still used for more than one quarter of ILI cases. Thus, further advances in spatial detection accuracy are dependant on systematic improvements in the collection of individual address information.

Malaria is highly endemic in the Democratic Republic of Congo (DRC), but the limits and intensity of transmission within the country are unknown. It is important to discern these patterns as well as the drivers which may underlie them in order for effective prevention measures to be carried out.

Environmental factors have been shown to be related to cholera and thus might prove useful for prediction. In Bangladesh and Vietnam, temporal cholera distributions are related to satellite-derived and in-situ environmental time series data in order to examine the relationships between cholera and the local environment. Ordered probit models examine associations in Bangladesh; probit models examine associations at 2 sites in Vietnam. Increases in ocean chlorophyll concentration are related to an increased magnitude of cholera in Bangladesh. Increases in sea surface temperature are most influential in Hue, Vietnam, whereas increases in river height have a significant role in Nha Trang, Vietnam. Cholera appearance and epidemic magnitude are related to the local environment. Local environmental parameters have consistent effects when cholera is regular and more prevalent in endemic settings, but in situations where cholera epidemics are rare there are differential environmental effects.

The spatio-temporal patterns of infectious diseases that are environmentally driven reflect the combined effects of transmission dynamics and environmental heterogeneity. They contain important information on different routes of transmission, including the role of environmental reservoirs. Consideration of the spatial component in infectious disease dynamics has led to insights on the propagation of fronts at the level of counties in rabies in the US, and the metapopulation behavior at the level of cities in childhood diseases such as measles in the UK, both at relatively coarse scales. As epidemiological data on individual infections become available, spatio-temporal patterns can be examined at higher resolutions.