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Problem Traditional random sampling at community level requires a list of every individual household that can be randomly selected in the study community. The longitudinal demographic surveillance systems often used as sampling frames are difficult to create in many resource-poor settings. Approach We used Google Earth imagery and geographical analysis software to develop a sampling frame. Every household structure within the catchment area was digitized and assigned coordinates. A random sample was then generated from the list of households. Local setting The sampling took place in Lilongwe, Malawi and formed a part of an investigation of the intensity of Plasmodium falciparum transmission in a multi-site Phase III trial of a candidate malaria vaccine. Relevant changes Creation of a complete list of household coordinates within the catchment area allowed us to generate a random sample representative of the population. Once the coordinates of the households in that sample had been entered into the hand- held receivers of a global positioning system device, the households could be accurately identified on the ground and approached. Lessons learnt In the development of a geographical sampling frame, the use of Google Earth satellite imagery and geographical software appeared to be an efficient alternative to the use of a demographic surveillance system. The use of a complete list of household coordinates reduced the time needed to locate households in the random sample. Our approach to generate a sampling frame is accurate, has utility beyond morbidity studies and appears to be a cost-effective option in resource-poor settings. [TEXT NOT REPRODUCIBLE IN ASCII] [TEXT NOT REPRODUCIBLE IN ASCII] Probleme L'echantillonnage aleatoire traditionnel au niveau de la communaute requiert une liste de tous les menages Individueis qui peuvent etre cholsis aleatoirement dans une etude communautaire. Les systemes de surveillance demographlque longitudlnaux, qui sont souvent utllises comme base d'echantlllonnage, sont diffidles a creer dans de nombreux endroits a falbles ressources. Approche Nous avons utlllse llmagerie de Google Earth et un loglciel d'analyse geographique pour developper une base d'echantillonnage. Chaque structure de menage dans la circonscription a ete numerisee et associee a des coordonnees. Un echantillon aleatoire a ensuite ete genere a partir de la liste des menages. Environnement local L'echantillonnage a ete effectue a Lilongwe, au Malawi, et entrait ans le cadre d'une etude sur l'intenslte de la transmission du Plasmodium falciparum dans un essai clinique multicentrique de phase III d'un vaccin contre le paludisme potentlel. Changements significatifs La creation d'une liste complete des coordonnees des menages dans la circonscription nous a permis de generer un echantillon aleatoire representatif de la population. Une fois que les coordonnees des menages de cet echantillon ont ete entrees dans les recepteurs portables d'un dlspositlf du systeme de positionnement universel, les menages ont pu etre predsement identifies et approches sur le terrain. Lecons tirees Dans le developpement d'une base d'echantillonnage geographique, l'utilisation de llmagerie satellite de Google Earth et d'un logiciel geographique semblait etre une alternative efncace a l'utilisation d'un systeme de surveillance demographique. L'utilisation d'une liste complete de coordonnees des menages a redult le temps necessaire pour localiser les menages dans un echantillon aleatoire. Notre approche de generation d'une base d'echantlllonnage est precise, utile au-dela des etudes de morbidlte et semble etre une option economique dans les endroits a faibles ressources. [TEXT NOT REPRODUCIBLE IN ASCII] Situacion El muestreo aleatorio tradicional a nivel comunitario requiere una lista de todos los hogares Individuales que pueden ser seleccionados al azar en la comunidad de estudio. Los sistemas de vigilancia demografica longitudinales que se utilizan a menudo como marcos de muestreo resultan dificiles de crear en muchos entornos con pocos recursos. Enfoque Empleamos imagenes de Google Earth y un software de analisis geografico para desarrollar un marco de muestreo. Se digitalizo y asignaron coordenadas a cada estructura familiar dentro de la zona de captacion, y luego se genero una muestra al azar a partir de la lista de los hogares. Marco regional El muestreo se llevo a cabo en Lilongwe (Malawi) y formo parte de una investigacion sobre la intensidad de la transmision del Plasmodium falciparum en un ensayo de fase III multicentrico de una posible vacuna contra la malaria. Cambios importantes La creacion de una lista completa de las coordenadas de los hogares dentro del area de influencia nos ha permitido generar una muestra aleatoria representativa de la poblacion. Una vez introducidas las coordenadas de los hogares en la muestra en los receptores portatiles de un dispositivo con un sistema de posicionamiento global, se pudo Identificar con precision a los hogares y aproximarse a estos en el terreno. Lecciones aprendidas En el desarrollo de un marco de muestreo geografico, el uso de imagenes de satelite de Google Earth y un software geografico resulto ser una alternativa eficaz a la utilizacion de un sistema de vigilancia demografica. La utilizacion de una lista completa de las coordenadas de los hogares reduce el tiempo necesario para localizar estos en la muestra aleatoria. Nuestro enfoque para generar un marco de muestreo es exacto, tiene una utilidad mas alla de los estudios de morbilidad y parece ser una opcion rentable en los entornos con recursos escasos., Problem In estimating disease prevalence at community level, a sampling frame is required to ensure that the study sample is representative of the study community. Such a sampling frame typically [...]

Abstract Background During the past three decades in Bangladesh, millions of tubewells have been installed to reduce the prevalence of diarrheal disease. This study evaluates the impacts of tubewell access and tubewell depth on childhood diarrhea in rural Bangladesh. Methods A total of 59,796 cases of diarrhea in children under 5 were recorded in 142 villages of Matlab, Bangladesh during monthly community health surveys between 2000 and 2006. The location and depth of 12,018 tubewells were surveyed in 2002-04 and integrated with diarrhea and other data in a geographic information system. A proxy for tubewell access was developed by calculating the local density of tubewells around households. Logistic regression models were built to examine the relationship between childhood diarrhea, tubewell density and tubewell depth. Wealth, adult female education, flood control, population density and the child's age were considered as potential confounders. Results Baris (patrilineally-related clusters of households) with greater tubewell density were associated with significantly less diarrhea (OR (odds ratio) = 0.87, 95% confidence interval (CI): 0.85-0.89). Tubewell density had a greater influence on childhood diarrhea in areas that were not protected from flooding. Baris using intermediate depth tubewells (140-300 feet) were associated with more childhood diarrhea (OR = 1.24, 95% CI: 1.19-1.29) than those using shallow wells (10-140 feet). Baris using deep wells (300-990 feet) had less diarrheal disease than those using shallow wells, however, the difference was significant only when population density was low (< 1000 person/km2) or children were at the age of 13-24 months. Conclusions Increased access to tubewells is associated with a lower risk of childhood diarrhea. Intermediate- depth wells are associated with more childhood diarrhea compared to shallower or deeper wells. These findings may have implications for on-going efforts to reduce exposure to elevated levels of arsenic contained in groundwater that is pumped in this study area primarily from shallow tubewells.

Abstract Background This study investigates the impact of tubewell user density on cholera and shigellosis events in Matlab, Bangladesh between 2002 and 2004. Household-level demographic, health, and water infrastructure data were incorporated into a local geographic information systems (GIS) database. Geographically-weighted regression (GWR) models were constructed to identify spatial variation of relationships across the study area. Zero-inflated negative binomial regression models were run to simultaneously measure the likelihood of increased magnitude of disease events and the likelihood of zero cholera or shigellosis events. The aim of this study was to examine the effect of tubewell density on both the occurrence of diarrheal disease and the magnitude of diarrheal disease incidence. Results In Matlab, households with greater tubewell density were more likely to report zero cholera or shigellosis events. Results for both cholera and shigellosis GWR models suggest that tubewell density effects are spatially stationary and the use of non-spatial statistical methods is appropriate. Conclusions Increasing the amount of drinking water available to households through increased density of tubewells contributed to lower reports of cholera and shigellosis events in rural Bangladesh. Our findings demonstrate the importance of tubewell installation and access to groundwater in reducing diarrheal disease events in the developing world.

Abstract Background Regional environmental factors have been shown to be related to cholera. Previous work in Bangladesh found that temporal patterns of cholera are positively related to satellite-derived environmental variables including ocean chlorophyll concentration (OCC). Methods This paper investigates whether local socio-economic status (SES) modifies the effect of regional environmental forces. The study area is Matlab, Bangladesh, an area of approximately 200,000 people with an active health and demographic surveillance system. Study data include (1) spatially-referenced demographic and socio-economic characteristics of the population; (2) satellite-derived variables for sea surface temperature (SST), sea surface height (SSH), and OCC; and (3) laboratory confirmed cholera case data for the entire population. Relationships between cholera, the environmental variables, and SES are measured using generalized estimating equations with a logit link function. Additionally two separate seasonal models are built because there are two annual cholera epidemics, one pre-monsoon, and one post-monsoon. Results SES has a significant impact on cholera occurrence: the higher the SES score, the lower the occurrence of cholera. There is a significant negative association between cholera incidence and SSH during the pre-monsoon period but not for the post-monsoon period. OCC is positively associated with cholera during the pre-monsoon period but not for the post-monsoon period. SST is not related to cholera incidence. Conclusions Overall, it appears cholera is influenced by regional environmental variables during the pre-monsoon period and by local-level variables (e.g., water and sanitation) during the post-monsoon period. In both pre- and post-monsoon seasons, SES significantly influences these patterns, likely because it is a proxy for poor water quality and sanitation in poorer households.

Objectives. We investigated whether deep tube wells installed to provide arsenic-free groundwater in rural Bangladesh have the added benefit of reducing childhood diarrheal disease incidence. Methods. We recorded cases of diarrhea in children younger than 5 years in 142 villages of Matlab, Bangladesh, during monthly community health surveys in 2005 and 2006. We surveyed the location and depth of 12 018 tube wells and integrated these data with diarrhea data and other data in a geographic information system. We fit a longitudinal logistic regression model to measure the relationship between childhood diarrhea and deep tube well use. We controlled for maternal education, family wealth, year, and distance to a deep tube well. Results. Household clusters assumed to be using deep tube wells were 48.7% (95% confidence interval = 27.8%, 63.5%) less likely to have a case of childhood diarrhea than were other household clusters. Conclusions. Increased access to deep tube wells may provide dual benefits to vulnerable populations in Matlab, Bangladesh, by reducing the risk of childhood diarrheal disease and decreasing exposure to naturally occurring arsenic in groundwater. [ABSTRACT FROM AUTHOR]

Background Millions of households throughout Bangladesh have been exposed to high levels of arsenic (As) causing various deadly diseases by drinking groundwater from shallow tubewells for the past 30 years. Well testing has been the most effective form of mitigation because it has induced massive switching from tubewells that are high (>50 μg/L) in As to neighboring wells that are low in As. A recent study has shown, however, that shallow low-As wells are more likely to be contaminated with the fecal indicator E. coli than shallow high-As wells, suggesting that well switching might lead to an increase in diarrheal disease. Methods Approximately 60,000 episodes of childhood diarrhea were collected monthly by community health workers between 2000 and 2006 in 142 villages of Matlab, Bangladesh. In this cross-sectional study, associations between childhood diarrhea and As levels in tubewell water were evaluated using logistic regression models. Results Adjusting for wealth, population density, and flood control by multivariate logistic regression, the model indicates an 11% (95% confidence intervals (CIs) of 4-19%) increase in the likelihood of diarrhea in children drinking from shallow wells with 10-50 μg/L As compared to shallow wells with >50 μg/L As. The same model indicates a 26% (95%CI: 9-42%) increase in diarrhea for children drinking from shallow wells with ≤10 μg/L As compared to shallow wells with >50 μg/L As. Conclusion Children drinking water from shallow low As wells had a higher prevalence of diarrhea than children drinking water from high As wells. This suggests that the health benefits of reducing As exposure may to some extent be countered by an increase in childhood diarrhea. [ABSTRACT FROM AUTHOR]