Journal Article > ResearchFull Text
Epidemics. 2015 September 3; Volume 14; 1-10.; DOI:10.1016/j.epidem.2015.08.001
Allan M, Grandesso F, Pierre R, Magloire R, Coldiron ME, et al.
Epidemics. 2015 September 3; Volume 14; 1-10.; DOI:10.1016/j.epidem.2015.08.001
BACKGROUND
Cholera is caused by Vibrio cholerae, and is transmitted through fecal-oral contact. Infection occurs after the ingestion of the bacteria and is usually asymptomatic. In a minority of cases, it causes acute diarrhea and vomiting, which can lead to potentially fatal severe dehydration, especially in the absence of appropriate medical care. Immunity occurs after infection and typically lasts 6-36 months. Cholera is responsible for outbreaks in many African and Asian developing countries, and caused localised and episodic epidemics in South America until the early 1990s. Haiti, despite its low socioeconomic status and poor sanitation, had never reported cholera before the recent outbreak that started in October 2010, with over 720,000 cases and over 8700 deaths (Case fatality rate: 1.2%) through 8 December 2014. So far, this outbreak has seen 3 epidemic peaks, and it is expected that cholera will remain in Haiti for some time.
METHODOLOGY/FINDINGS
To trace the path of the early epidemic and to identify hot spots and potential transmission hubs during peaks, we examined the spatial distribution of cholera patients during the first two peaks in Artibonite, the second-most populous department of Haiti. We extracted the geographic origin of 84,000 patients treated in local health facilities between October 2010 and December 2011 and mapped these addresses to 63 rural communal sections and 9 urban cities. Spatial and cluster analysis showed that during the first peak, cholera spread along the Artibonite River and the main roads, and sub-communal attack rates ranged from 0.1% to 10.7%. During the second peak, remote mountain areas were most affected, although sometimes to very different degrees even in closely neighboring locations. Sub-communal attack rates during the second peak ranged from 0.2% to 13.7%. The relative risks at the sub-communal level during the second phase showed an inverse pattern compared to the first phase.
CONCLUSION/SIGNIFICANCE
These findings demonstrate the value of high-resolution mapping for pinpointing locations most affected by cholera, and in the future could help prioritize the places in need of interventions such as improvement of sanitation and vaccination. The findings also describe spatio-temporal transmission patterns of the epidemic in a cholera-naïve country such as Haiti. By identifying transmission hubs, it is possible to target prevention strategies that, over time, could reduce transmission of the disease and eventually eliminate cholera in Haiti.
Cholera is caused by Vibrio cholerae, and is transmitted through fecal-oral contact. Infection occurs after the ingestion of the bacteria and is usually asymptomatic. In a minority of cases, it causes acute diarrhea and vomiting, which can lead to potentially fatal severe dehydration, especially in the absence of appropriate medical care. Immunity occurs after infection and typically lasts 6-36 months. Cholera is responsible for outbreaks in many African and Asian developing countries, and caused localised and episodic epidemics in South America until the early 1990s. Haiti, despite its low socioeconomic status and poor sanitation, had never reported cholera before the recent outbreak that started in October 2010, with over 720,000 cases and over 8700 deaths (Case fatality rate: 1.2%) through 8 December 2014. So far, this outbreak has seen 3 epidemic peaks, and it is expected that cholera will remain in Haiti for some time.
METHODOLOGY/FINDINGS
To trace the path of the early epidemic and to identify hot spots and potential transmission hubs during peaks, we examined the spatial distribution of cholera patients during the first two peaks in Artibonite, the second-most populous department of Haiti. We extracted the geographic origin of 84,000 patients treated in local health facilities between October 2010 and December 2011 and mapped these addresses to 63 rural communal sections and 9 urban cities. Spatial and cluster analysis showed that during the first peak, cholera spread along the Artibonite River and the main roads, and sub-communal attack rates ranged from 0.1% to 10.7%. During the second peak, remote mountain areas were most affected, although sometimes to very different degrees even in closely neighboring locations. Sub-communal attack rates during the second peak ranged from 0.2% to 13.7%. The relative risks at the sub-communal level during the second phase showed an inverse pattern compared to the first phase.
CONCLUSION/SIGNIFICANCE
These findings demonstrate the value of high-resolution mapping for pinpointing locations most affected by cholera, and in the future could help prioritize the places in need of interventions such as improvement of sanitation and vaccination. The findings also describe spatio-temporal transmission patterns of the epidemic in a cholera-naïve country such as Haiti. By identifying transmission hubs, it is possible to target prevention strategies that, over time, could reduce transmission of the disease and eventually eliminate cholera in Haiti.
Journal Article > ResearchFull Text
BMC Public Health. 2012 June 18; Volume 12 (Issue 1); 442.; DOI:10.1186/1471-2458-12-442
Fernandez MAL, Schomaker M, Mason PR, Fesselet JF, Baudot Y, et al.
BMC Public Health. 2012 June 18; Volume 12 (Issue 1); 442.; DOI:10.1186/1471-2458-12-442
BACKGROUND
In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009.
METHODS
We developed an ecological study using secondary data. First, we described attack rates by suburb and then calculated rate ratios using whole Harare as reference. We illustrated the average elevation and cholera cases by suburbs using geographical information. Finally, we estimated a generalized linear mixed model (under the assumption of a Poisson distribution) with an Empirical Bayesian approach to model the relation between the risk of cholera and the elevation in meters in Harare. We used a random intercept to allow for spatial correlation of neighboring suburbs.
RESULTS
This study identifies a spatial pattern of the distribution of cholera cases in the Harare epidemic, characterized by a lower cholera risk in the highest elevation suburbs of Harare. The generalized linear mixed model showed that for each 100 meters of increase in the topographical elevation, the cholera risk was 30% lower with a rate ratio of 0.70 (95% confidence interval=0.66-0.76). Sensitivity analysis confirmed the risk reduction with an overall estimate of the rate ratio between 20% and 40%.
CONCLUSION
This study highlights the importance of considering topographical elevation as a geographical and environmental risk factor in order to plan cholera preventive activities linked with water and sanitation in endemic areas. Furthermore, elevation information, among other risk factors, could help to spatially orientate cholera control interventions during an epidemic.
In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009.
METHODS
We developed an ecological study using secondary data. First, we described attack rates by suburb and then calculated rate ratios using whole Harare as reference. We illustrated the average elevation and cholera cases by suburbs using geographical information. Finally, we estimated a generalized linear mixed model (under the assumption of a Poisson distribution) with an Empirical Bayesian approach to model the relation between the risk of cholera and the elevation in meters in Harare. We used a random intercept to allow for spatial correlation of neighboring suburbs.
RESULTS
This study identifies a spatial pattern of the distribution of cholera cases in the Harare epidemic, characterized by a lower cholera risk in the highest elevation suburbs of Harare. The generalized linear mixed model showed that for each 100 meters of increase in the topographical elevation, the cholera risk was 30% lower with a rate ratio of 0.70 (95% confidence interval=0.66-0.76). Sensitivity analysis confirmed the risk reduction with an overall estimate of the rate ratio between 20% and 40%.
CONCLUSION
This study highlights the importance of considering topographical elevation as a geographical and environmental risk factor in order to plan cholera preventive activities linked with water and sanitation in endemic areas. Furthermore, elevation information, among other risk factors, could help to spatially orientate cholera control interventions during an epidemic.
Journal Article > ResearchFull Text
Sci Rep. 2021 December 13; Volume 11 (Issue 1); 23868.; DOI:10.1038/s41598-021-03301-z
Ochoa C, Pittavino M, Martins SB, Alcoba G, Bolon I, et al.
Sci Rep. 2021 December 13; Volume 11 (Issue 1); 23868.; DOI:10.1038/s41598-021-03301-z
Most efforts to understand snakebite burden in Nepal have been localized to relatively small areas and focused on humans through epidemiological studies. We present the outcomes of a geospatial analysis of the factors influencing snakebite risk in humans and animals, based on both a national-scale multi-cluster random survey and, environmental, climatic, and socio-economic gridded data for the Terai region of Nepal. The resulting Integrated Nested Laplace Approximation models highlight the importance of poverty as a fundamental risk-increasing factor, augmenting the snakebite odds in humans by 63.9 times. For animals, the minimum temperature of the coldest month was the most influential covariate, increasing the snakebite odds 23.4 times. Several risk hotspots were identified along the Terai, helping to visualize at multiple administrative levels the estimated population numbers exposed to different probability risk thresholds in 1 year. These analyses and findings could be replicable in other countries and for other diseases.