Veronica Escamilla

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.

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.

Fecal Contamination of Shallow Tubewells in Bangladesh Inversely Related to Arsenic

The health risks of As exposure due to the installation of millions of shallow tubewells in the Bengal Basin are known, but fecal contamination of shallow aquifers has not systematically been examined. This could be a source of concern in densely populated areas with poor sanitation because the hydraulic travel time from surface water bodies to shallow wells that are low in As was previously shown to be considerably shorter than for shallow wells that are high in As. In this study, 125 tubewells 6−36 m deep were sampled in duplicate for 18 months to quantify the presence of the fecal indicator Escherichia coli. On any given month, E. coli was detected at levels exceeding 1 most probable number per 100 mL in 19−64% of all shallow tubewells, with a higher proportion typically following periods of heavy rainfall. The frequency of E. coli detection averaged over a year was found to increase with population surrounding a well and decrease with the As content of a well, most likely because of downward transport of E. coli associated with local recharge. The health implications of higher fecal contamination of shallow tubewells, to which millions of households in Bangladesh have switched in order to reduce their exposure to As, need to be evaluated.

Local population and regional environmental drivers of cholera in Bangladesh

BackgroundRegional 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).MethodsThis 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.ResultsSES 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.ConclusionsOverall, 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.

Impact of population and latrines on fecal contamination of ponds in rural Bangladesh

A majority of households in Bangladesh rely on pond water for hygiene. Exposure to pond water fecal contamination could therefore still contribute to diarrheal disease despite the installation of numerous tubewells for drinking. The objectives of this study are to determine the predominant sources (human or livestock) of fecal pollution in ponds and examine the association between local population, latrine density, latrine quality and concentrations of fecal bacteria and pathogens in pond water. Forty-three ponds were analyzed for E. coli using culture-based methods and E. coli, Bacteroidales and adenovirus using quantitative PCR. Population and sanitation spatial data were collected and measured against pond fecal contamination. Humans were the dominant source of fecal contamination in 79% of the ponds according to Bacteroidales measurements. Ponds directly receiving latrine effluent had the highest concentrations of fecal indicator bacteria (up to 10⁶ Most Probable Number (MPN) of culturable E. coli per 100 mL). Concentrations of fecal indicator bacteria correlated with population surveyed within a distance of 30-70 m (p<0.05) and total latrines surveyed within 50-70 m (p<0.05). Unsanitary latrines (visible effluent or open pits) within the pond drainage basin were also significantly correlated to fecal indicator concentrations (p<0.05). Water in the vast majority of the surveyed ponds contained unsafe levels of fecal contamination attributable primarily to unsanitary latrines, and to lesser extent, to sanitary latrines and cattle. Since the majority of fecal pollution is derived from human waste, continued use of pond water could help explain the persistence of diarrheal disease in rural South Asia.

Implications of Fecal Bacteria Input from Latrine-Polluted Ponds for Wells in Sandy Aquifers

Ponds receiving latrine effluents may serve as sources of fecal contamination to shallow aquifers tapped by millions of tube-wells in Bangladesh. To test this hypothesis, transects of monitoring wells radiating away from four ponds were installed in a shallow sandy aquifer underlying a densely populated village and monitored for 14 months. Two of the ponds extended to medium sand. Another pond was sited within silty sand and the last in silt. The fecal indicator bacterium E. coli was rarely detected along the transects during the dry season and was only detected near the ponds extending to medium sand up to 7 m away during the monsoon. A log-linear decline in E. coli and Bacteroidales concentrations with distance along the transects in the early monsoon indicates that ponds excavated in medium sand were the likely source of contamination. Spatial removal rates ranged from 0.5 to 1.3 log(10)/m. After the ponds were artificially filled with groundwater to simulate the impact of a rain storm, E. coli levels increased near a pond recently excavated in medium sand, but no others. These observations show that adjacent sediment grain-size and how recently a pond was excavated influence the how much fecal contamination ponds receiving latrine effluents contribute to neighboring groundwater.

Influence of Latrine Proximity and Type on Tubewell Water Quality and Diarrheal Disease in Bangladesh

Diarrheal diseases are endemic in Bangladesh, where sanitation is poor, and untreated drinking water extracted from shallow (<43 m) tubewells could partially contribute to disease propagation. This study measures the effects of local population–environment context on tubewell water quality and diarrheal disease incidence. The study site includes six villages in Matlab, Bangladesh, with approximately 12,000 residents. Study data include monthly Escherichia coli concentrations for 100 wells, monthly diarrheal events for all children under five, and a detailed water and sanitation infrastructure database created through a submeter accuracy Global Positioning System survey. We developed sanitation metrics to measure the relationship between tubewell water fecal contamination and estimates of human fecal loadings at varying scales. The relationship between childhood diarrhea and E. coli in drinking water was measured for households that obtained drinking water from survey wells. Results show that tubewells surrounded by unsanitary latrines, latrine-polluted ponds, and higher population densities were more frequently contaminated with fecal coliforms. The analysis also showed that poor sanitation infrastructure might affect childhood diarrheal disease via tubewell contamination. Our findings shed light on the importance of integrating population and environment data to identify circumstances in which shallow well water quality is compromised and children are put at risk of contracting diarrheal diseases. Sanitation interventions should highlight the spatial separation of latrines and drinking water wells to limit contamination.

Effect of deep tube well use on childhood diarrhoea in Bangladesh

OBJECTIVE To determine whether the installation of deep tube wells to reduce exposure to groundwater arsenic in rural Bangladesh had an effect on the incidence of childhood diarrhoeal disease. METHODS Episodes of diarrhoeal disease in children aged under 5 years that occurred on one specified day each month between 2005 and 2006 were reported to community health workers for six rural villages. A geographical information system containing details of household water use and sanitation in the villages was built using data obtained by a global positioning system survey. The information system also included health, spatial and demographic data. A field survey was carried out to determine whether households obtained drinking water from deep tube wells installed in 2005. The effect of deep tube well use on the incidence of childhood diarrhoea was assessed using a random effects negative binomial regression model. FINDINGS The risk of childhood diarrhoea was 46% lower in the 179 households that used a deep tube well than in the 364 that used a shallow tube well (P=0.032). Neither socioeconomic status, latrine density, population density nor study year had a significant influence on disease risk. The incidence of childhood diarrhoea declined dramatically between 2005 and 2006, irrespective of water source. CONCLUSION The introduction of deep tube wells to reduce arsenic in drinking water in rural Bangladesh had the additional benefit of lowering the incidence of diarrhoea among young children.

Diarrheal disease risk in rural Bangladesh decreases as tubewell density increases: a zero- inflated and geographically weighted analysis

BackgroundThis 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.ResultsIn 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.ConclusionsIncreasing 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.

Sampling at community level by using satellite imagery and geographical analysis

Abstract 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.