Michael Emch

Herd immunity conferred by killed oral cholera vaccines in Bangladesh: A reanalysis

BACKGROUND Decisions about the use of killed oral cholera vaccines, which confer moderate levels of direct protection to vaccinees, can depend on whether the vaccines also provide indirect (herd) protection when high levels of vaccine coverage are attained. We reanalysed data from a field trial in Bangladesh to ascertain whether there is evidence of indirect protection from killed oral cholera vaccines. METHODS We analysed the first year of surveillance data from a placebo-controlled trial of B subunit-killed whole-cell and killed whole-cell-only oral cholera vaccines in children and adult women in Bangladesh. We calculated whether there was an inverse, monotonic trend for the relation between the level of vaccine coverage in a residential cluster and the incidence of cholera in individual vaccine recipients or placebo recipients residing in the cluster after controlling for potential confounding variables. FINDINGS Vaccine coverage of the targeted population ranged from 4% to 65%. Incidence rates of cholera among placebo recipients were inversely related to levels of vaccine coverage (7.01 cases per 1000 in the lowest quintile of coverage vs 1.47 cases per 1000 in the highest quintile; p<0.0001 for trend). Receipt of vaccine by an individual and the level of vaccine coverage of the individuals cluster were independently related to a reduced risk of cholera. Moreover, after adjustment for the level of vaccine coverage of the cluster, vaccine protective efficacy remained significant (55% [95% CI 41-66], p<0.0001). INTERPRETATION In addition to providing direct protection to vaccine recipients, killed oral cholera vaccines confer significant herd protection to neighbouring non-vaccinated individuals. Use of these vaccines could have a major effect on the burden of cholera in endemic settings.

Enhancing spatial detection accuracy for syndromic surveillance with street level incidence data

BackgroundThe 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.MethodsInfluenza-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.ResultsRelative 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.ConclusionsSpatial 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.

Perinatal exposure to hazardous air pollutants and autism spectrum disorders at age 8.

Background: Hazardous air pollutants are plausible candidate exposures for autism spectrum disorders. They have been explored in recent studies for their role in the development of these disorders. Methods: We used a prevalent case-control design to screen perinatal exposure to 35 hazardous air pollutants for further investigation in autism etiology. We included 383 children with autism spectrum disorders and, as controls, 2829 children with speech and language impairment. All participants were identified from the records-based surveillance of 8-year-old children conducted by the Autism and Developmental Disabilities Monitoring Network in North Carolina (for children born in 1994 and 1996) and West Virginia (born in 1992 and 1994). Exposures to ambient concentrations of metal, particulate, and volatile organic air pollutants in the census tract of the childs birth residence were assigned from the 1996 National Air Toxics Assessment annual-average model. We estimated odds ratios (ORs) for autism spectrum disorders and corresponding 95% confidence intervals (CIs), comparing across the 20th and 80th percentiles of log-transformed hazardous air pollutant concentration among the selected controls, using semi-Bayes logistic models and adjusting for sampling variables (surveillance year and state), a priori demographic confounders from the birth certificate and census, and covarying air pollutants. Results: We estimated many near-null ORs, including those for metals, established human neurodevelopmental toxicants, and several pollutants that were elevated in a similar study in California. Hazardous air pollutants with more precise and elevated OR estimates included methylene chloride, 1.4 (95% CI = 0.7–2.5), quinoline, 1.4 (1.0–2.2), and styrene, 1.8 (1.0–3.1). Conclusions: Our screening design was limited by exposure misclassification of air pollutants and the use of an alternate developmental disorder as the control group, both of which may have biased results toward the null. Despite these limitations, methylene chloride, quinoline, and styrene emerged (based on this analysis and prior epidemiologic evidence) as candidates that warrant further investigation for a possible role in autism etiology.

Evolution of highly pathogenic H5N1 avian influenza viruses in Vietnam between 2001 and 2007

Highly pathogenic avian influenza (HPAI) H5N1 viruses have caused dramatic economic losses to the poultry industry of Vietnam and continue to pose a serious threat to public health. As of June 2008, Vietnam had reported nearly one third of worldwide laboratory confirmed human H5N1 infections. To better understand the emergence, spread and evolution of H5N1 in Vietnam we studied over 300 H5N1 avian influenza viruses isolated from Vietnam since their first detection in 2001. Our phylogenetic analyses indicated that six genetically distinct H5N1 viruses were introduced into Vietnam during the past seven years. The H5N1 lineage that evolved following the introduction in 2003 of the A/duck/Hong Kong/821/2002-like viruses, with clade 1 hemagglutinin (HA), continued to predominate in southern Vietnam as of May 2007. A virus with a clade 2.3.4 HA newly introduced into northern Vietnam in 2007, reassorted with pre-existing clade 1 viruses, resulting in the emergence of novel genotypes with neuraminidase (NA) and/or internal gene segments from clade 1 viruses. A total of nine distinct genotypes have been present in Vietnam since 2001, including five that were circulating in 2007. At least four of these genotypes appear to have originated in Vietnam and represent novel H5N1 viruses not reported elsewhere. Geographic and temporal analyses of H5N1 infection dynamics in poultry suggest that the majority of viruses containing new genes were first detected in northern Vietnam and subsequently spread to southern Vietnam after reassorting with pre-existing local viruses in northern Vietnam. Although the routes of entry and spread of H5N1 in Vietnam remain speculative, enhanced poultry import controls and virologic surveillance efforts may help curb the entry and spread of new HPAI viral genes.

Seasonality of cholera from 1974 to 2005: A review of global patterns

BackgroundThe 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.Data, Methods, and ResultsCholera data are compiled from 1974 to 2005 from the World Health Organization Weekly Epidemiological Reports, a database that includes all reported cholera cases in 140 countries. The data are analyzed to measure whether season, latitude, and their interaction are significantly associated with the country-level number of outbreaks in each of the 12 preceding months using separate negative binomial regression models for northern, southern, and combined hemispheres. Likelihood ratios tests are used to determine the model of best fit. The results suggest that cholera outbreaks demonstrate seasonal patterns in higher absolute latitudes, but closer to the equator, cholera outbreaks do not follow a clear seasonal pattern.ConclusionThe findings suggest that environmental and climatic factors partially control the temporal variability of cholera. These results also indirectly contribute to the growing debate about the effects of climate change and global warming. As climate change threatens to increase global temperature, resulting rises in sea levels and temperatures may influence the temporal fluctuations of cholera, potentially increasing the frequency and duration of cholera outbreaks.

Diarrheal disease risk in Matlab, Bangladesh

The objective of this research project is to assess risk for diarrheal disease in rural Bangladesh by analyzing the complex and dynamic interaction of biological, socioeconomic, cultural/behavioral and environmental factors over time and space. Risk factors of cholera and non-cholera water diarrheal disease are calculated to compare the relative importance of risk for several independent variables. Diarrheal disease data were collected for people who were hospitalized at the International Centre for Diarrhoeal Disease Research (ICDDR) hospital from January 1, 1992 to December 31, 1994. Using laboratory and hospital records, cases were assigned to one of two diarrhea disease categories (cholera or non-cholera watery diarrhea) that were used as dependent variables in the analysis stage of the research. Age-matched individuals were randomly chosen from the community to be controls. Information was collected for independent variables that were hypothesized to be related to watery diarrhea. This information was collected by administering questionnaires, obtaining secondary data from the ICDDRs demographic surveillance system records and community health worker record books and calculating variables using a geographic information system database. Sanitation and water availability and use are extremely important in the effort to reduce secondary cholera and non-cholera, watery diarrhea transmission. Water use and availability variables were more important for non-cholera watery diarrheal risk than for cholera but nevertheless they were important for both. Socioeconomic status is an important indirect cause of both of these diseases because poverty is the root cause of many of the other variables, such as lack of sanitation and clean water. Flood-control was related to both types of diarrhea but it is not understood why. Since the Bangladesh Flood Action Plan will continue to build and maintains flood-control embankments, it is important to investigate whether there is a pattern to this relationship throughout the country and to investigate why the relationship exists.

Comparison of fecal indicators with pathogenic bacteria and rotavirus in groundwater

Groundwater is routinely analyzed for fecal indicators but direct comparisons of fecal indicators to the presence of bacterial and viral pathogens are rare. This study was conducted in rural Bangladesh where the human population density is high, sanitation is poor, and groundwater pumped from shallow tubewells is often contaminated with fecal bacteria. Five indicator microorganisms (E. coli, total coliform, F+RNA coliphage, Bacteroides and human-associated Bacteroides) and various environmental parameters were compared to the direct detection of waterborne pathogens by quantitative PCR in groundwater pumped from 50 tubewells. Rotavirus was detected in groundwater filtrate from the largest proportion of tubewells (40%), followed by Shigella (10%), Vibrio (10%), and pathogenic E. coli (8%). Spearman rank correlations and sensitivity-specificity calculations indicate that some, but not all, combinations of indicators and environmental parameters can predict the presence of pathogens. Culture-dependent fecal indicator bacteria measured on a single date did not predict total bacterial pathogens, but annually averaged monthly measurements of culturable E. coli did improve prediction for total bacterial pathogens. A qPCR-based E. coli assay was the best indicator for the bacterial pathogens. F+RNA coliphage were neither correlated nor sufficiently sensitive towards rotavirus, but were predictive of bacterial pathogens. Since groundwater cannot be excluded as a significant source of diarrheal disease in Bangladesh and neighboring countries with similar characteristics, the need to develop more effective methods for screening tubewells with respect to microbial contamination is necessary.

Identifying environmental risk factors for endemic cholera: a raster GIS approach

The bacteria that cause cholera are known to be normal inhabitants of surface water, however, the environmental risk factors for different biotypes of cholera are not well understood. This study identifies environmental risk factors for cholera in an endemic area of Bangladesh using a geographic information systems (GIS) approach. The study data were collected from a longitudinal health and demographic surveillance system and the data were integrated within a geographic information system database of the research area. Two study periods were chosen because they had different dominant biotypes of the disease. From 1992 to 1996 El Tor cholera was dominant and from 1983 to 1987 classical cholera was dominant. The study found the same three risk factors for the two biotypes of cholera including proximity to surface water, high population density, and poor educational level. The GIS database was used to measure the risk factors and spatial filtering techniques were employed. These robust spatial methods are offered as an example for future epidemiological research efforts that define environmental risk factors for infectious diseases.

The spatial epidemiology of cholera in an endemic area of Bangladesh

This paper defines high-risk areas of cholera based on environmental risk factors of the disease in an endemic area of Bangladesh. The risk factors include proximity to surface water, high population density, and low educational status, which were identified in an earlier study by the authors. Cholera data were analyzed by spatially referenced extended household units for two time periods, 1983-1987 and 1992-1996. These periods were chosen because they had different dominant cholera agents. From 1983-1987 classical cholera was dominant and from 1992-1996 El Tor was dominant. By defining high-risk areas based on risk factors, this study builds a spatial risk model for cholera. The model is then evaluated based on the locations of observed cholera cases. The study also identifies the determinants of death due to cholera for the two different time periods dominated by the different cholera agents. The modeled risk areas that were based on the risk factors were found to correspond with actual distributions of cholera morbidity and mortality. The high-risk areas of the dominant cholera agents are relatively stable over time. However, from 1983-1987 El Tor cholera, which was not the dominant agent during that period, was not associated with high-risk areas, suggesting that the El Tor habitat may have changed over time. The case fatality rate for cholera was related to proximity to a diarrhea treatment hospital in the study area.

Highly localized sensitivity to climate forcing drives endemic cholera in a megacity

The population dynamics of endemic cholera in urban environments—in particular interannual variation in the size and distribution of seasonal outbreaks—remain poorly understood and highly unpredictable. In part, this situation is due to the considerable demographic, socioeconomic, and environmental heterogeneity of large and growing urban centers. Despite this heterogeneity, the influence of climate variability on the population dynamics of infectious diseases is considered a large-scale, regional, phenomenon, and as such has been previously addressed for cholera only with temporal models that do not incorporate spatial structure. Here we show that a probabilistic spatial model can explain cholera dynamics in the megacity of Dhaka, Bangladesh, and afford a basis for cholera forecasts at lead times of 11 mo. Critically, we find that the action of climate variability (El Niño southern oscillation and flooding) is quite localized: There is a climate-sensitive urban core that acts to propagate risk to the rest of the city. The modeling framework presented here should be applicable to cholera in other cities, as well as to other infectious diseases in urban settings and other biological systems with spatiotemporal interactions.