44 research outputs found
The Geography of Groundwater Quality and Childhood Diarrheal Disease in Bangladesh
Childhood diarrhea persists in Bangladesh despite efforts to shift from surface water to groundwater for drinking. It is unknown whether shallow aquifer groundwater extracted through tubewells is a significant source of disease or if other sources such as surface water and local sanitation are driving transmission. Using the disease ecology framework, this study explores the influence of poor sanitation on diarrheal disease transmission. Specific questions addressed in this study include: 1) Does poor sanitation influence shallow tubewell water quality? 2) Does fecal contamination of tubewells influence diarrheal disease? 3) Does the neighborhood water and sanitation infrastructure affect childhood diarrheal disease incidence above and beyond household factors? 4) Does poor sanitation influence diarrheal disease via bathing ponds? 5) Does obtaining drinking water from deep tubewells have a protective effect against childhood diarrhea incidence? This study integrates groundwater microbial data, health and demographic surveillance data, and detailed spatial data of the water and sanitation infrastructure in six villages in Matlab, Bangladesh. The relationship between groundwater quality and poor sanitation is measured at multiple scales using geographic analysis tools. Direct and indirect sanitation influences on childhood diarrheal disease (2002-2006) are explored using neighborhood latrine metrics, and bathing pond latrine metrics. A deep tubewell arsenic mitigation intervention is also examined to determine whether children drinking from deep tubewells experience less diarrhea than children drinking from shallow wells. Results suggest that poor sanitation is predictive of both groundwater contamination and diarrheal disease. Children living in neighborhoods with insufficient access to septic latrines experience higher diarrhea incidence. Additionally, children living near bathing ponds surrounded by latrines leaking effluent also have a higher incidence. While deep tubewells were installed for arsenic mitigation, they are also protective against diarrheal disease. These results shed light on the importance of integrating population and environment data to identify particular circumstances in which groundwater is compromised and children are at risk of contracting diarrheal diseases. These results suggest that poor sanitation diminishes the effect of improved drinking water sources and improvements to the built sanitation infrastructure are needed to reduce diarrheal disease incidence.Doctor of Philosoph
Late-Stage Breast Cancer Diagnosis and Health Care Access in Illinois∗
The variations of breast cancer mortality rates from place to place reflect both underlying differences in breast cancer prevalence and differences in diagnosis and treatment that affect the risk of death. This article examines the role of access to health care in explaining the variation of late-stage diagnosis of breast cancer. We use cancer registry data for the state of Illinois by zip code to investigate spatial variation in late diagnosis. Geographic information systems and spatial analysis methods are used to create detailed measures of spatial access to health care such as convenience of visiting primary care physicians and travel time from the nearest mammography facility. The effects of spatial access, in combination with the influences of socioeconomic factors, on late-stage breast cancer diagnosis are assessed using statistical methods. The results suggest that for breast cancer, poor geographical access to primary health care significantly increases the risk of late diagnosis for persons living outside the city of Chicago. Disadvantaged population groups including those with low income and racial and ethnic minorities tend to experience high rates of late diagnosis. In Illinois, poor spatial access to primary health care is more strongly associated with late diagnosis than is spatial access to mammography. This suggests the importance of primary care physicians as gatekeepers in early breast cancer detection
Diarrheal disease risk in rural Bangladesh decreases as tubewell density increases: a zero-inflated and geographically weighted analysis
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
Impact of tubewell access and tubewell depth on childhood diarrhea in Matlab, Bangladesh
<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p><it>Baris </it>(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. <it>Baris </it>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). <it>Baris </it>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/km<sup>2</sup>) or children were at the age of 13-24 months.</p> <p>Conclusions</p> <p>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.</p
Influence of Detection Method and Study Area Scale on Syphilis Cluster Identification in North Carolina
Identifying geographical clusters of sexually transmitted infections can aid in targeting prevention and control efforts. However, detectable clusters can vary between detection methods because of different underlying assumptions. Furthermore, because disease burden is not geographically homogenous, the reference population is sensitive to the study area scale, affecting cluster outcomes. We investigated the influence of cluster detection method and geographical scale on syphilis cluster detection in Mecklenburg County, North Carolina
Sampling at community level by using satellite imagery and geographical analysis
AbstractProblemTraditional 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.ApproachWe 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 settingThe 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 changesCreation 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 learntIn 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
Sex Differences in Interpersonal Violence in Malawi: Analysis of a Hospital-Based Trauma Registry
Although interpersonal violence (“assault”) exists in every society, the World Health Organization (WHO) estimated that 90 % of the exposure burden occurs in low- and middle-income countries. The objectives of this study were to define the incidence of assault-related injuries among subjects presenting for emergency room care secondary to sustained trauma in Lilongwe, Malawi; to measure the impact of sex on incidence, injury type, and care received; and to measure the effect of both sex and geographic location of the injury on time to presentation for medical care
Protective Benefits of Deep Tube Wells Against Childhood Diarrhea in Matlab, Bangladesh
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
Local population and regional environmental drivers of cholera in Bangladesh
<p>Abstract</p> <p>Background</p> <p>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).</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p
Distance to testing sites and its association with timing of HIV diagnosis *
Early HIV diagnosis enables prompt treatment initiation, thereby contributing to decreased morbidity, mortality, and transmission. We aimed to describe the association between distance from residence to testing sites and HIV disease stage at diagnosis. Using HIV surveillance data, we identified all new HIV diagnoses made at publicly-funded testing sites in central North Carolina during 2005-2013. Early-stage HIV was defined as acute HIV (antibody-negative test with a positive HIV RNA) or recent HIV (normalized optical density <0.8 on the BED assay for non-AIDS cases); remaining diagnoses were considered post-early-stage HIV. Street distance between residence at diagnosis and 1) the closest testing site and 2) the diagnosis site was dichotomized at 5 miles. We fit log-binomial models using generalized estimating equations to estimate prevalence ratios (PR) and robust 95% CI for post-early-stage diagnoses by distance. Models were adjusted for race/ethnicity and testing period. Most of the 3028 new diagnoses were black (N=2144; 70.8%), men who have sex with men (N=1685; 55.7%), and post-early-stage HIV diagnoses (N=2010; 66.4%). Overall, 1145 (37.8%) cases traveled <5 miles for a diagnosis. Among cases traveling ≥5 miles for a diagnosis, 1273 (67.6%) lived <5 miles from a different site. Residing ≥5 miles from a testing site was not associated with post-early-stage HIV (adjusted PR, 95% CI: 0.98, 0.92-1.04), but traveling ≥5 miles for a diagnosis was associated with higher post-early HIV prevalence (1.07, 1.02-1.13). Most of the elevated prevalence observed in cases traveling ≥5 miles for a diagnosis occurred among those living <5 miles from a different site (1.09, 1.03-1.16). Modest increases in post-early-stage HIV diagnosis were apparent among persons living near a site, but choosing to travel longer distances to test. Understanding reasons for increased travel distances could improve accessibility and acceptability of HIV services and increase early diagnosis rates