Spatial dependency of V. cholera prevalence on open space refuse dumps in Kumasi, Ghana: a spatial statistical modelling

Knowledge, Attitudes, Practices, and Determinants Towards Wastewater Management in Northwest Ethiopia: A Community-Based Cross-Sectional Study

Background

Globally, waste management has been a major public health problem. Public knowledge, attitudes, practices (KAP) and participation are key elements of any waste management program. In Ethiopia, however, the level of KAP and associated factors regarding wastewater management (WWM) at the household level are not well studied and understood. This study was, therefore, conducted to assess the knowledge, attitude, practice and associated factors of wastewater management (WWM) among the residents in Gondar town, Ethiopia.

Methods

A community-based cross-sectional study was conducted during March and April, 2016. A total of 422 participants were selected using the systematic random sampling technique. A structured questionnaire was employed to collect data which were entered and analyzed using the Statistical Package for Social Science (SPSS) version 20. A multivariable binary logistic regression analysis was used to ascertain the significance of associations at <0.05 p-value and the adjusted odds ratio (AOR) with a 95% confidence interval (CI).

Results

Among 422 study participants included, 63.5%, 43.4%, and 48.6% of them had good knowledge, attitudes, and self-reported practices regarding WWM, respectively. Knowledge of participants was significantly associated with house rent (AOR 1.12, 95% CI (1.22, 3.69), civil servant (AOR 5.47, 95% CI (1.87, 8.02), and positive attitudes (AOR 2.69, 95% CI (1.68, 4.30), while space availability (AOR 1.84, 95% CI (1.23, 2.75), and good knowledge (AOR 2.46, 95% CI (1.61, 3.77) were associated factors of attitudes. Moreover, good knowledge (AOR 1.32, 95% CI (1.87, 2.02), and positive attitudes (AOR 1.03, 95% CI (1.01, 2.34) were significantly associated factors of self-reported practices.

Conclusion

Limited knowledge, attitudes and practices were seen among study population. A great emphasis on improvement of knowledge, attitudes and practices towards WWM is necessary. Moreover, it would be better to qualitatively explore variables which explain the qualitative attributes of the community, like community Attitudes and knowledge.

Particulate matter exposure predicts residence in high-risk areas for community acquired pneumonia among hospitalized children

Particulate matter exposure is a risk factor for lower respiratory tract infection in children. Here, we investigated the geospatial patterns of community-acquired pneumonia and the impact of PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) on geospatial variability of pneumonia in children. We performed a retrospective analysis of prospectively collected population-based surveillance study data of community-acquired pneumonia hospitalizations among children <18 years residing in the Memphis metropolitan area, who were enrolled in the Centers for Disease Control and Prevention sponsored Etiology of Pneumonia in the Community (EPIC) study from January 2010 to June 2012. The outcome measure, residence in high- and low-risk areas for community-acquired pneumonia, was determined by calculating pneumonia incidence rates and performing cluster analysis to identify areas with higher/lower than expected rates of community-acquired pneumonia for the population at risk. High PM_2.5 was defined as exposure to PM_2.5 concentrations greater than the mean value (>10.75 μg/m³), and low PM_2.5 is defined as exposure to PM_2.5 concentrations less than or equal to the mean value (≤10.75 μg/m³). We also assessed the effects of age, sex, race/ethnicity, history of wheezing, insurance type, tobacco smoke exposure, bacterial etiology, and viral etiology of infection. Of 810 (96.1%) subjects with radiographic community-acquired pneumonia, who resided in the Memphis metropolitan area and had addresses which were successfully geocoded (Supplementary Figure F2), 220 (27.2%) patients were identified to be from high- (n = 126) or low-risk (n = 94) community-acquired pneumonia areas. Community-acquired pneumonia in Memphis metropolitan area had a non-homogenous geospatial pattern. PM_2.5 was associated with residence in high-risk areas for community-acquired pneumonia. In addition, children with private insurance and bacterial, as opposed to viral, etiology of infection had a decreased risk of residence in a high-risk area for community-acquired pneumonia. The results from this paper suggest that environmental exposures as well as social risk factors are associated with childhood pneumonia.

The cholera risk assessment in Kano State, Nigeria: A historical review, mapping of hotspots and evaluation of contextual factors

Nigeria is endemic for cholera since 1970, and Kano State report outbreaks annually with high case fatality ratios ranging from 4.98%/2010 to 5.10%/2018 over the last decade. However, interventions focused on cholera prevention and control have been hampered by a lack of understanding of hotspot Local Government Areas (LGAs) that trigger and sustain yearly outbreaks. The goal of this study was to identify and categorize cholera hotspots in Kano State to inform a national plan for disease control and elimination in the State. We obtained LGA level confirmed and suspected cholera data from 2010 to 2019 from the Nigeria Centre for Disease Control (NCDC) and Kano State Ministry of Health. Data on inland waterbodies and population numbers were obtained from online sources and NCDC, respectively. Clusters (hotspots) were identified using SaTScan through a retrospective analysis of the data for the ten-year period using a Poisson discrete space-time scan statistic. We also used a method newly proposed by the Global Task Force on Cholera Control (GTFCC) to identify and rank hotspots based on two epidemiological indicators including mean annual incidence per 100 000 population of reported cases and the persistence of cholera for the study period. In the ten-year period, 16,461 cholera cases were reported with a case fatality ratio of 3.32% and a mean annual incidence rate of 13.4 cases per 100 000 population. Between 2010 and 2019, the most severe cholera exacerbations occurred in 2014 and 2018 with annual incidence rates of 58.01 and 21.52 cases per 100 000 inhabitants, respectively. Compared to 2017, reported cases and deaths increased by 214.56% and 406.67% in 2018. The geographic distribution of outbreaks revealed considerable spatial heterogeneity with the widest in 2014. Space-time clustering analysis identified 18 out of 44 LGAs as high risk for cholera (hotspots) involving both urban and rural LGAs. Cholera clustered around water bodies, and the relative risk of having cholera inside the hotspot LGA were 1.02 to 3.30 times higher than elsewhere in the State. A total of 4,894,144 inhabitants were in these hotspots LGAs. Of these, six LGAs with a total population of 1.665 million had a relative risk greater than 2 compared to the state as a whole. The SaTScan (statistical) and GTFCC methods were in agreement in hotspots identification. This study identified cholera hotspots LGAs in Kano State from 2010-2019. Hotspots appeared in both urban and rural settings. Focusing control strategies on these hotspots will facilitate control and eliminate cholera from the State.

Predicting Urban Waterlogging Risks by Regression Models and Internet Open-Data Sources

In the context of climate change and rapid urbanization, urban waterlogging risks due to rainstorms are becoming more frequent and serious in developing countries. One of the most important means of solving this problem lies in elucidating the roles played by the spatial factors of urban surfaces that cause urban waterlogging, as well as in predicting urban waterlogging risks. We applied a regression model in ArcGIS with internet open-data sources to predict the probabilities of urban waterlogging risks in Hanoi, Vietnam, during the period 2012–2018 by considering six spatial factors of urban surfaces: population density (POP-Dens), road density (Road-Dens), distances from water bodies (DW-Dist), impervious surface percentage (ISP), normalized difference vegetation index (NDVI), and digital elevation model (DEM). The results show that the frequency of urban waterlogging occurrences is positively related to the first four factors but negatively related to NDVI, and DEM is not an important explanatory factor in the study area. The model achieved a good modeling effect and was able to explain the urban waterlogging risk with a confidence level of 67.6%. These results represent an important analytic step for urban development strategic planners in optimizing the spatial factors of urban surfaces to prevent and control urban waterlogging.

Identifying Infectious Diarrhea Hot spots and Associated Socioeconomic Factors in Anhui Province, China

Infectious diarrhea cases have increased during the past years in the Anhui Province of China, but little is known about its spatial cluster pattern and associated socioeconomic factors. We obtained county-level total cases of infectious diarrhea in 105 counties of Anhui in 2016 and computed age-adjusted rates. Socioeconomic factors were collected from the Statistical Yearbook. Hot spot analysis was used to identify hot and cold spot counties for infectious diarrhea incidence. We then applied binary logistic regression models to determine the association between socioeconomic factors and hot spot or cold spot clustering risk. Hot spot analysis indicated there were both significant hot spot (29 counties) and cold spot (18 counties) clustering areas for infectious diarrhea in Anhui (P < 0.10). Multivariate binary logistic regression results showed that infectious diarrhea hot spots were positively associated with per capita gross domestic product (GDP), with an adjusted odds ratio (AOR): 3.51, 95% CI: 2.09-5.91, whereas cold spots clustering were positively associated with the number of medical staffs (AOR: 1.18, 95% CI: 1.08-1.29) and negatively associated with the number of public health physicians (AOR: 0.27, 95% CI: 0.09-0.86). We identified locations for hot and cold spot clusters of infectious diarrhea incidence in Anhui, and the clustering risks were significantly associated with health workforce resources and the regional economic development. Targeted interventions should be carried out with considerations of regional socioeconomic conditions.

The multi-sectorial emergency response to a cholera outbreak in Internally Displaced Persons camps in Borno State, Nigeria, 2017

Introduction

In August 2017, a cholera outbreak started in Muna Garage Internally Displaced Persons camp, Borno state, Nigeria and >5000 cases occurred in six local government areas. This qualitative study evaluated perspectives about the emergency response to this outbreak.

Methods

We conducted 39 key informant interviews and focus group discussions, and reviewed 21 documents with participants involved with surveillance, water, sanitation, hygiene, case management, oral cholera vaccine (OCV), communications, logistics and coordination. Qualitative data analysis used thematic techniques comprising key words in context, word repetition and key sector terms.

Results

Authorities were alerted quickly, but outbreak declaration took 12 days due to a 10-day delay waiting for culture confirmation. Outbreak investigation revealed several potential transmission channels, but a leaking latrine around the index cases' house was not repaired for more than 7 days. Chlorine was initially not accepted by the community due to rumours that it would sterilise women. Key messages were in Hausa, although Kanuri was the primary local language; later this was corrected. Planning would have benefited using exercise drills to identify weaknesses, and inventory sharing to avoid stock outs. The response by the Rural Water Supply and Sanitation Agency was perceived to be slow and an increased risk from a religious festival was not recognised. Case management was provided at treatment centres, but some partners were concerned that their work was not recognised asking, 'Who gets the glory and the data?' Nearly one million people received OCV and its distribution benefited from a robust infrastructure for polio vaccination. There was initial anxiety, rumour and reluctance about OCV, attributed by many to lack of formative research prior to vaccine implementation. Coordination was slow initially, but improved with activation of an emergency operations centre (EOC) that enabled implementation of incident management system to coordinate multisectoral activities and meetings held at 16:00 hours daily. The synergy between partners and government improved when each recognised the government's leadership role.

Conclusion

Despite a timely alert of the outbreak, delayed laboratory confirmation slowed initial response. Initial responses to the outbreak were not well coordinated but improved with the EOC. Understanding behaviours and community norms through rapid formative research should improve the effectiveness of the emergency response to a cholera outbreak. OCV distribution was efficient and benefited from the polio vaccine infrastructure.

21st century research in urban WASH and health in sub-Saharan Africa: methods and outcomes in transition

Tackling global inequalities in access to Water, Sanitation and Hygiene (WASH) remains an urgent issue - 58% of annual diarrhoeal deaths are caused by inadequate WASH provision. A global context of increasing urbanisation, changing demographics and health transitions demands an understanding and impact of WASH on a broad set of health outcomes. We examine the literature, in terms of health outcomes, considering WASH access and interventions in urban sub-Saharan Africa from 2000 to 2017. Our review of studies which evaluate the effectiveness of specific WASH interventions, reveals an emphasis of WASH research on acute communicable diseases, particularly diarrhoeal diseases. In contrast, chronic communicable and non-communicable health outcomes were notable gaps in the literature as well as a lack of focus on cross-cutting issues, such as ageing, well-being and gender equality. We recommend a broader focus of WASH research and interventions in urban Africa to better reflect the demographic and health transitions happening. Abbreviations: CBA: Controlled Before and After; GSD: Government Service Delivery; IWDSSD: International Drinking-Water, Supply and Sanitation Decade (IDWSSD); KAP: Knowledge, Attitudes and Practices; IBD: Irritable Bowel Diseases; MDG: Millennium Development Goals; NTD: Neglected Tropical Diseases; PSSD: Private Sector Service Delivery; SDG: Sustainable Development Goals; SSA: Sub Saharan Africa; SODIS: Solar Disinfection System; STH: Soil Transmitted Helminths; RCT: Randomised Control Trial; WASH: Water Sanitation and Hygiene; WHO: World Health Organization.

Syndromic survey and molecular analysis of influenza viruses at the human-swine interface in two West African cosmopolitan cities suggest the possibility of bidirectional interspecies transmission

Influenza viruses are frequently transmitted between pigs and their handlers, and among pig handlers. However, reports on socio-environmental variables as potential risk factors associated with transmission of influenza in West African swine production facilities are very scarce. Syndromic survey for influenza was therefore conducted in Ibadan, Nigeria, and Kumasi, Ghana, in order to identify and elucidate selected socio-environmental variables that may contribute to the occurrence and distribution of influenza-like illness (ILI) among swine industry workers. In addition, molecular analyses were conducted to elucidate the nature of influenza viruses circulating at the human-swine interface in these cities and better understand the dynamics of their transmission. Influenza viruses were detected by type-specific and subtype-specific RT-PCR. Sequencing and phylogenetic analyses were carried out. Socio-environmental variables were tested by both univariable and multivariable regression methods for significance at p < 0.05. Three risk factors for ILI were identified in each city. These included "frequency of visit of pig handler to pig pen or lairage" (Ibadan: risk ratio [RR] = 1.54, 95% confidence interval [CI] = 1.36-1.79, p = 0.02; Kumasi: RR = 1.28, 95% CI = 1.11-1.71, p = 0.01) and "pig handler's awareness about biosecurity measures" (Ibadan: RR = 7.09, 95% CI = 2.36-21.32, p < 0.001; Kumasi: RR = 4.84, 95% CI = 1.98-11.80, p < 0.001). Influenza A(H1N1)pdm09 viruses, with M genes closely related to those which circulated among pigs in the two cities during the same period, were detected among Nigerian and Ghanaian pig industry workers. These findings suggest the possibility of bidirectional transmission of influenza at the human-swine interface in these cities and underscore the need for more extensive molecular studies. Risk factors identified may assist in the control of human-to-human and human-to-swine transmission of influenza in the West African swine industry.

Experience and Future Perceived Risk of Floods and Diarrheal Disease in Urban Poor Communities in Accra, Ghana

Diarrheal disease is a critical health condition in urban areas of developing countries due to increasing urbanization and its associated problems of sanitation and poor access to good drinking water. Increasing floods in cities have been linked to the risk of diarrheal disease. There are few studies that specifically link flooding with diarrhea diseases. This may be due to the fact that secondary data mainly hospital recorded cases, and not individual cases at the household level are used. Furthermore, of the few papers that consider the flood-diarrheal diseases nexus, none have considered risk perceptions in general, and more specifically, whether households that have experienced floods which resulted in a reported case of diarrhea, have higher perceived risks of future occurrences of the two phenomena compared to households that had different experiences. Yet, this is critical for the development of interventions that seek to increase protective behaviors and reduce the risk of contracting diarrhea. We surveyed 401 households in some selected urban poor communities in Accra, the capital of Ghana. Results show that households that experienced floods which resulted in a reported case of diarrhea, have higher perceived risk of future occurrence of the two phenomena compared to other households. We recommend public education that reduces the risk of exposure to flood and diarrhea through flood mitigation measures, including the construction of drains in communities and educating communities on good sanitation.

Spatial, temporal, and spatiotemporal analysis of under-five diarrhea in Southern Ethiopia

Background

Despite improvements in prevention efforts, childhood diarrhea remains a public health concern. However, there may be substantial variation influenced by place, time, and season. Description of diarrheal clusters in time and space and understanding seasonal patterns can improve surveillance and management. The present study investigated the spatial and seasonal distribution and purely spatial, purely temporal, and space-time clusters of childhood diarrhea in Southern Ethiopia.

Methods

The study was a retrospective analysis of data from the Health Management Information System (HMIS) under-five diarrheal morbidity reports from July 2011 to June 2017 in Sidama Zone. Annual diarrhea incidence at district level was calculated. Incidence rate calculation and seasonal trend analysis were performed. The Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant special, temporal, and space-time diarrhea clusters. ArcGIS 10.1 was used to plot the maps.

Results

A total of 202,406 under-five diarrheal cases with an annual case of 5822 per 100,000 under-five population were reported. An increasing trend of diarrhea incidence was observed over the 6 years with seasonal variation picking between February and May. The highest incidence rate (135.8/1000) was observed in the year 2016/17 in Boricha district. One statistically significant most likely spatial cluster (Boricha district) and six secondary clusters (Malga, Hulla, Aleta Wondo, Shebedino, Loka Abaya, Dale, and Wondogenet) were identified. One statistically significant temporal cluster (LLR = 2109.93, p < 0.001) during December 2013 to May 2015 was observed in all districts. Statistically significant spatiotemporal primary hotspot was observed in December 2012 to January 2015 in Malga district with a likelihood ratio of 1214.67 and a relative risk of 2.03. First, second, third, and fourth secondary hotspots occurred from January 2012 to May 2012 in Loka Abaya, December 2011 in Bursa, from March to April 2014 in Gorchie, and March 2012 in Wonsho districts.

Conclusion

Childhood diarrhea was not distributed randomly over space and time and showed an overall increasing trend of seasonal variation peaking between February and May. The health department and other stakeholders at various levels need to plan targeted interventional activities at hotspot seasons and areas to reduce morbidity and mortality.

Waterborne disease outbreak detection: an integrated approach using health administrative databases

Hundreds of waterborne disease outbreaks (WBDO) of acute gastroenteritis (AGI) due to contaminated tap water are reported in developed countries each year. Such outbreaks are probably under-detected. The aim of our study was to develop an integrated approach to detect and study clusters of AGI in geographical areas with homogeneous exposure to drinking water. Data for the number of AGI cases are available at the municipality level while exposure to tap water depends on drinking water networks (DWN). These two geographical units do not systematically overlap. This study proposed to develop an algorithm which would match the most relevant grouping of municipalities with a specific DWN, in order that tap water exposure can be taken into account when investigating future disease outbreaks. A space-time detection method was applied to the grouping of municipalities. Seven hundred and fourteen new geographical areas (groupings of municipalities) were obtained compared with the 1,310 municipalities and the 1,706 DWN. Eleven potential WBDO were identified in these groupings of municipalities. For ten of them, additional environmental investigations identified at least one event that could have caused microbiological contamination of DWN in the days previous to the occurrence of a reported WBDO.

Correlates of domestic waste management and related health outcomes in Sunyani, Ghana: a protocol towards enhancing policy

BACKGROUND

Domestic waste generation has contributed significantly to hampering national waste management efforts. It poses serious threat to national development and requires proper treatment and management within and outside households. The problem of improper waste management has always been a challenge in Ghana, compelling several national surveys to report on the practice of waste management. However, little is known about how much waste is generated and managed within households and there is a serious dearth of information for national policy and planning. This paper seeks to document the handling and practice of waste management, including collection, storage, transportation and disposal along with the types and amount of waste generated by Households and their related health outcome.

METHODS

The study was a descriptive cross-sectional study and used a multi-stage sampling technique to sample 700 households. The study was planned and implemented from January to May 2015. It involved the use of structured questionnaires in the data collection over the period. Factors such as demographic characteristics, amount of waste generated, types of waste bins used within households, waste recycling, cost of disposing waste, and distance to dumpsite were all assessed.

RESULTS

The paper shows that each surveyed household generated 0.002 t of waste per day, of which 29% are both organic and inorganic. Though more than half of the respondents (53.6%) had positive attitude towards waste management, only 29.1% practiced waste management. The study reveals that there is no proper management of domestic waste except in few households that segregate waste. The study identified several elements as determinants of waste management practice. Female respondents were less likely to practice waste management (AOR 0.45; 95% Cl 0.29, 0.79), household size also determined respondents practice (AOR 0.26; Cl 0.09, 0.77). Practice of recycling (AOR 0.03; Cl 0.02, 0.08), distance to dumpsite (AOR 0.45; Cl 0.20, 0.99), were all significant predictors of waste management practice. Cholera which is a hygiene related disease was three times more likely to determine households' waste management practice (AOR 3.22; Cl 1.33, 7.84).

CONCLUSION

Considering the low waste management practice among households, there is the need for improved policy and enhanced education on proper waste management practice among households.

Geospatial Assessment of Cholera in a Rapidly Urbanizing Environment

This study mapped out and investigated the spatial relationship between cholera incidences and environmental risk factors in the study area. The study area was stratified into eight zones. Water samples from each zone were collected and analyzed to determine the colony forming units. GIS layers including housing density, digitized roads, rivers, buildings, and cholera incidence data from hospital archives were also collected and analyzed using ArcGIS 10.1. It was observed that there was an association between the ERFs (p < 0.001). Similarly, 18 out of the 44 waste dump sites, seven out of 18 markets, and two out of 36 abattoirs were found near the historical cholera cases. Similarly, 4 (21.1%) locations were traced to be predominantly close to rivers and waste dump site. All the historical cholera cases were found adjoining to roads and buildings. Highest CFU count was found in the wells and streams of areas with a cluster of all the environmental risk factors and high housing density. This study revealed that waste dump sites and market had the highest predisposing attribute while the least was abattoir. The uniqueness of the study lies in the combination of mapping and microbial analyses to identify and assess the pattern of cholera risk and also to provide clear information for development of strategies for environmental supervision.

A REACTION–DIFFUSION MODEL FOR THE CONTROL OF CHOLERA EPIDEMIC

Understanding the spatio-temporal dynamics of cholera outbreaks may help in devising more effective control procedures. In this paper, we have considered a reaction–diffusion system for biological control of cholera epidemic. Firstly, we have focused on temporal evolution of cholera in a region and its control using lytic bacteriophage in the aquatic reservoirs. Then, we have explored the effect of spatial dispersion of populations on the disease dynamics. We have observed the onset of sustained oscillations via Hopf-bifurcation for the endemic state of temporal system. This onset of fluctuations in populations depends upon the phage adsorption rate. But in the spatially extended setting, all the populations stabilize i.e., the spatio-temporal distribution of all the populations becomes uniform. Some numerical computations have been done to verify analytical results.

Childhood Diarrhea Exhibits Spatiotemporal Variation in Northwest Ethiopia: A SaTScan Spatial Statistical Analysis

BACKGROUND

Childhood diarrhea continues to be a public health problem in developing countries, including Ethiopia. Detecting clusters and trends of childhood diarrhea is important to designing effective interventions. Therefore, this study aimed to investigate spatiotemporal clustering and seasonal variability of childhood diarrhea in northwest Ethiopia.

METHODS

Retrospective record review of childhood diarrhea was conducted using quarterly reported data to the district health office for the seven years period beginning July 1, 2007. Thirty three districts were included and geo-coded in this study. Spatial, temporal and space-time scan spatial statistics were employed to identify clusters of childhood diarrhea. Smoothing using a moving average was applied to visualize the trends and seasonal pattern of childhood diarrhea. Statistical analyses were performed using Excel® and SaTScan programs. The maps were plotted using ArcGIS 10.0.

RESULTS

Childhood diarrhea in northwest Ethiopia exhibits statistical evidence of spatial, temporal, and spatiotemporal clustering, with seasonal patterns and decreasing temporal trends observed in the study area. A most likely purely spatial cluster was found in the East Gojjam administrative zone of Gozamin district (LLR = 7123.89, p <0.001). The most likely spatiotemporal cluster was detected in all districts of East Gojjam zone and a few districts of the West Gojjam zone (LLR = 24929.90, p<0.001), appearing from July 1, 2009 to June 30, 2011. One high risk period from July 1, 2008 to June 30, 2010 (LLR = 9655.86, p = 0.001) was observed in all districts. Peak childhood diarrhea cases showed a seasonal trend, occurring more frequently from January to March and April to June.

CONCLUSION

Childhood diarrhea did not occur at random. It has spatiotemporal variation and seasonal patterns with a decreasing temporal trend. Accounting for the spatiotemporal variation identified in the study areas is advised for the prevention and control of diarrhea.

A rapid assessment of drinking water quality in informal settlements after a cholera outbreak in Nairobi, Kenya

Populations living in informal settlements with inadequate water and sanitation infrastructure are at risk of epidemic disease. In 2010, we conducted 398 household surveys in two informal settlements in Nairobi, Kenya with isolated cholera cases. We tested source and household water for free chlorine residual (FCR) and Escherichia coli in approximately 200 households. International guidelines are ≥0.5 mg/L FCR at source, ≥0.2 mg/L at household, and <1 E. coli/100 mL. In these two settlements, 82% and 38% of water sources met FCR guidelines; and 7% and 8% were contaminated with E. coli, respectively. In household stored water, 82% and 35% met FCR guidelines and 11% and 32% were contaminated with E. coli, respectively. Source water FCR≥0.5 mg/L (p=0.003) and reported purchase of a household water treatment product (p=0.002) were associated with increases in likelihood that household stored water had ≥0.2 mg/L FCR, which was associated with a lower likelihood of E. coli contamination (p<0.001). These results challenge the assumption that water quality in informal settlements is universally poor and the route of disease transmission, and highlight that providing centralized water with ≥0.5 mg/L FCR or (if not feasible) household water treatment technologies reduces the risk of waterborne cholera transmission in informal settlements.

Spatial epidemiology of HIV-hepatitis co-infection in the State of Michigan: a cohort study

BACKGROUND

Acquired immunodeficiency syndrome (AIDS) is a continuing global public health threat affecting millions of individuals. In 2009, 33.3 million people worldwide were living with human immunodeficiency virus (HIV) infection. HIV-infected individuals are at an increased risk of acquiring hepatitis B and hepatitis C viral (HBV, HCV)infections because of shared transmission routes. The purpose of this study was to identify geographical clusters of HIV-(HBV/HCV) co-infection in the State of Michigan.

METHODS

Retrospective cohort data on HIV-infected individuals were matched to all hepatitis B and C cases in Michigan during the period of January 1, 2006 through December 31, 2009. A prevalence map of HIV infection was created and spatial clusters of HIV-hepatitis B or C co-infection were detected using GeoDa's bivariate local Moran's I and SaTScan's discrete Poisson model.

RESULTS

A bivariate cluster of high prevalence HIV and hepatitis B or C was identified in the Detroit Metropolitan Area and surrounding counties. A Poisson cluster of HIV-hepatitis B or C co-infection was identified, relative risk (RR) = 1.38 (p = 0.029) in the western and northwestern counties of Lower Michigan, controlling for sex, race, and AIDS status.

CONCLUSION

This study identified elevated HIV-hepatitis B or C co-infection unexplained by sex, race or AIDS status in counties outside of the Detroit Metropolitan Area where HIV prevalence was highest in Michigan. The findings from this study may be used to target future public health policy and healthcare interventions for HIV-hepatitis co-infection in these areas.

Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China

BACKGROUND

Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China.

METHODS

A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences.

RESULTS

Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences.

CONCLUSIONS

Although this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.

Fine scale Spatial-temporal cluster analysis for the infection risk of Schistosomiasis japonica using space-time scan statistics

Background

Marching towards the elimination of schistosomiasis in China, both the incidence and prevalence have witnessed profound decline over the past decades, with the strategy shifting from morbidity control to transmission control. The current challenge is to find out hotspots of transmission risk for precise targeted control in low-prevalence areas. This study assessed the risk at the village level, using the spatial and temporal characteristics of Schistosomiasis japonica in Anhui province from 2006 to 2012.

Method

The comprehensive database was generated from annual surveillance data at village level in Anhui province between 2006 and 2012, comprising schistosomiasis prevalence among humans and cattle, occurrence rate of infected environments and incidence rate of acute schistosomiasis. The database parameters were matched with geographic data of the study area and fine scale spatial-temporal cluster analysis based on retrospective space-time scan statistics was used to assess the clustering pattern of schistosomiasis. The analysis was conducted by using SaTScan 9.1.1 and ArcGIS 10.0. A spatial statistical modelling was carried out to determine the spatial dependency of prevalence of human infection by using Geoda 1.4.3.

Result

A pronounced decline was found in the prevalence of human infection, cattle infection, occurrence rate of environment with infected vector snails and incidence rate of acute schistosomiasis from 2006 to 2012 by 48.6%, 71.5%, 91.9% and 96.4%, respectively. Meanwhile, all 4 indicators showed a statistically significant clustering pattern both in time and space, with a total of 16, 6, 8 and 4 corresponding clustering foci found respectively. However, the number of clustering foci declined with time, and none was found after year 2010. All clustering foci were mainly distributed along the Yangtze River and its connecting branches. The result shows that there is a direct spatial relationship between prevalence of human infection and the other indicators.

Conclusion

A decreasing trend in space-time clustering of schistosomiasis endemic status was observed between 2006 and 2012 in Anhui province. Nevertheless, giving the complexity in schistosomiasis control, areas within the upper-stream of Yangtze River in Anhui section and its connecting branches should be targeted for effective implementation of control strategies in the future.

Domestic waste disposal practice and perceptions of private sector waste management in urban Accra

BACKGROUND

Waste poses a threat to public health and the environment if it is not stored, collected, and disposed of properly. The perception of waste as an unwanted material with no intrinsic value has dominated attitudes towards disposal. This study investigates the domestic waste practices, waste disposal, and perceptions about waste and health in an urban community.

METHODS

The study utilised a mixed-method approach. A cross-sectional survey questionnaire and in-depth interview were used to collect data. A total of 364 household heads were interviewed in the survey and six key informants were interviewed with the in-depth interviews.

RESULTS

The results of the study revealed that 93.1% of households disposed of food debris as waste and 77.8% disposed of plastic materials as waste. The study also showed that 61.0% of the households disposed of their waste at community bins or had waste picked up at their homes by private contractors. The remaining 39.0% disposed of their waste in gutters, streets, holes and nearby bushes. Of those who paid for the services of private contractors, 62.9% were not satisfied with the services because of their cost and irregular collection. About 83% of the respondents were aware that improper waste management contributes to disease causation; most of the respondents thought that improper waste management could lead to malaria and diarrhoea. There was a general perception that children should be responsible for transporting waste from the households to dumping sites.

CONCLUSION

Proper education of the public, the provision of more communal trash bins, and the collection of waste by private contractors could help prevent exposing the public in municipalities to diseases.

Environmental determinants of cholera outbreaks in inland Africa: a systematic review of main transmission foci and propagation routes

Cholera is generally regarded as the prototypical waterborne and environmental disease. In Africa, available studies are scarce, and the relevance of this disease paradigm is questionable. Cholera outbreaks have been repeatedly reported far from the coasts: from 2009 through 2011, three-quarters of all cholera cases in Africa occurred in inland regions. Such outbreaks are either influenced by rainfall and subsequent floods or by drought- and water-induced stress. Their concurrence with global climatic events has also been observed. In lakes and rivers, aquatic reservoirs of Vibrio cholerae have been evocated. However, the role of these reservoirs in cholera epidemiology has not been established. Starting from inland cholera-endemic areas, epidemics burst and spread to various environments, including crowded slums and refugee camps. Human displacements constitute a major determinant of this spread. Further studies are urgently needed to better understand these complex dynamics, improve water and sanitation efforts, and eliminate cholera from Africa.

Spatio-temporal dynamics of cholera during the first year of the epidemic in Haiti

BACKGROUND

In October 2010, cholera importation in Haiti triggered an epidemic that rapidly proved to be the world's largest epidemic of the seventh cholera pandemic. To establish effective control and elimination policies, strategies rely on the analysis of cholera dynamics. In this report, we describe the spatio-temporal dynamics of cholera and the associated environmental factors.

METHODOLOGY/PRINCIPAL FINDINGS

Cholera-associated morbidity and mortality data were prospectively collected at the commune level according to the World Health Organization standard definition. Attack and mortality rates were estimated and mapped to assess epidemic clusters and trends. The relationships between environmental factors were assessed at the commune level using multivariate analysis. The global attack and mortality rates were 488.9 cases/10,000 inhabitants and 6.24 deaths/10,000 inhabitants, respectively. Attack rates displayed a significantly high level of spatial heterogeneity (varying from 64.7 to 3070.9 per 10,000 inhabitants), thereby suggesting disparate outbreak processes. The epidemic course exhibited two principal outbreaks. The first outbreak (October 16, 2010-January 30, 2011) displayed a centrifugal spread of a damping wave that suddenly emerged from Mirebalais. The second outbreak began at the end of May 2011, concomitant with the onset of the rainy season, and displayed a highly fragmented epidemic pattern. Environmental factors (river and rice fields: p<0.003) played a role in disease dynamics exclusively during the early phases of the epidemic.

CONCLUSION

Our findings demonstrate that the epidemic is still evolving, with a changing transmission pattern as time passes. Such an evolution could have hardly been anticipated, especially in a country struck by cholera for the first time. These results argue for the need for control measures involving intense efforts in rapid and exhaustive case tracking.

Clinical, epidemiological, and spatial characteristics of Vibrio parahaemolyticus diarrhea and cholera in the urban slums of Kolkata, India

Background

There is not much information on the differences in clinical, epidemiological and spatial characteristics of diarrhea due to V. cholerae and V. parahaemolyticus from non-coastal areas. We investigated the differences in clinical, epidemiological and spatial characteristics of the two Vibrio species in the urban slums of Kolkata, India.

Methods

The data of a cluster randomized cholera vaccine trial were used. We restricted the analysis to clusters assigned to placebo. Survival analysis of the time to the first episode was used to analyze risk factors for V. parahaemolyticus diarrhea or cholera. A spatial scan test was used to identify high risk areas for cholera and for V. parahaemolyticus diarrhea.

Results

In total, 54,519 people from the placebo clusters were assembled. The incidence of cholera (1.30/1000/year) was significantly higher than that of V. parahaemolyticus diarrhea (0.63/1000/year). Cholera incidence was inversely related to age, whereas the risk of V. parahaemolyticus diarrhea was age-independent. The seasonality of diarrhea due to the two Vibrio species was similar. Cholera was distinguished by a higher frequency of severe dehydration, and V. parahaemolyticus diarrhea was by abdominal pain. Hindus and those who live in household not using boiled or treated water were more likely to have V. parahaemolyticus diarrhea. Young age, low socioeconomic status, and living closer to a project healthcare facility were associated with an increased risk for cholera. The high risk area for cholera differed from the high risk area for V. parahaemolyticus diarrhea.

Conclusion

We report coexistence of the two vibrios in the slums of Kolkata. The two etiologies of diarrhea had a similar seasonality but had distinguishing clinical features. The risk factors and the high risk areas for the two diseases differ from one another suggesting different modes of transmission of these two pathogens.

Bayesian structured additive regression modeling of epidemic data: application to cholera

Background

A significant interest in spatial epidemiology lies in identifying associated risk factors which enhances the risk of infection. Most studies, however, make no, or limited use of the spatial structure of the data, as well as possible nonlinear effects of the risk factors.

Methods

We develop a Bayesian Structured Additive Regression model for cholera epidemic data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulations. The model is applied to cholera epidemic data in the Kumasi Metropolis, Ghana. Proximity to refuse dumps, density of refuse dumps, and proximity to potential cholera reservoirs were modeled as continuous functions; presence of slum settlers and population density were modeled as fixed effects, whereas spatial references to the communities were modeled as structured and unstructured spatial effects.

Results

We observe that the risk of cholera is associated with slum settlements and high population density. The risk of cholera is equal and lower for communities with fewer refuse dumps, but variable and higher for communities with more refuse dumps. The risk is also lower for communities distant from refuse dumps and potential cholera reservoirs. The results also indicate distinct spatial variation in the risk of cholera infection.

Conclusion

The study highlights the usefulness of Bayesian semi-parametric regression model analyzing public health data. These findings could serve as novel information to help health planners and policy makers in making effective decisions to control or prevent cholera epidemics.

Cholera epidemic in Guinea-Bissau (2008): the importance of "place"

BACKGROUND

As resources are limited when responding to cholera outbreaks, knowledge about where to orient interventions is crucial. We describe the cholera epidemic affecting Guinea-Bissau in 2008 focusing on the geographical spread in order to guide prevention and control activities.

METHODOLOGY/PRINCIPAL FINDINGS

We conducted two studies: 1) a descriptive analysis of the cholera epidemic in Guinea-Bissau focusing on its geographical spread (country level and within the capital); and 2) a cross-sectional study to measure the prevalence of houses with at least one cholera case in the most affected neighbourhood of the capital (Bairro Bandim) to detect clustering of households with cases (cluster analysis). All cholera cases attending the cholera treatment centres in Guinea-Bissau who fulfilled a modified World Health Organization clinical case definition during the epidemic were included in the descriptive study. For the cluster analysis, a sample of houses was selected from a satellite photo (Google Earth™); 140 houses (and the four closest houses) were assessed from the 2,202 identified structures. We applied K-functions and Kernel smoothing to detect clustering. We confirmed the clustering using Kulldorff's spatial scan statistic. A total of 14,222 cases and 225 deaths were reported in the country (AR = 0.94%, CFR = 1.64%). The more affected regions were Biombo, Bijagos and Bissau (the capital). Bairro Bandim was the most affected neighborhood of the capital (AR = 4.0). We found at least one case in 22.7% of the houses (95%CI: 19.5-26.2) in this neighborhood. The cluster analysis identified two areas within Bairro Bandim at highest risk: a market and an intersection where runoff accumulates waste (p<0.001).

CONCLUSIONS/SIGNIFICANCE

Our analysis allowed for the identification of the most affected regions in Guinea-Bissau during the 2008 cholera outbreak, and the most affected areas within the capital. This information was essential for making decisions on where to reinforce treatment and to guide control and prevention activities.

Assessing the relationship between socioeconomic conditions and urban environmental quality in Accra, Ghana

The influence of socioeconomic status (SES) on health inequalities is widely known, but there is still poor understanding of the precise relationship between area-based socioeconomic conditions and neighborhood environmental quality. This study aimed to investigate the socioeconomic conditions which predict urban neighbourhood environmental quality. The results showed wide variation in levels of association between the socioeconomic variables and environmental conditions, with strong evidence of a real difference in environmental quality across the five socioeconomic classes with respect to total waste generation (p < 0.001), waste collection rate (p < 0.001), sewer disposal rate (p < 0.001), non-sewer disposal (p < 0.003), the proportion of households using public toilets (p = 0.005). Socioeconomic conditions are therefore important drivers of change in environmental quality and urban environmental interventions aimed at infectious disease prevention and control if they should be effective could benefit from simultaneous implementation with other social interventions.

A scan statistic for continuous data based on the normal probability model

Temporal, spatial and space-time scan statistics are commonly used to detect and evaluate the statistical significance of temporal and/or geographical disease clusters, without any prior assumptions on the location, time period or size of those clusters. Scan statistics are mostly used for count data, such as disease incidence or mortality. Sometimes there is an interest in looking for clusters with respect to a continuous variable, such as lead levels in children or low birth weight. For such continuous data, we present a scan statistic where the likelihood is calculated using the the normal probability model. It may also be used for other distributions, while still maintaining the correct alpha level. In an application of the new method, we look for geographical clusters of low birth weight in New York City.

Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand

BACKGROUND

Diarrhea is a major public health problem in Thailand. The Ministry of Public Health, Thailand, has been trying to monitor and control this disease for many years. The methodology and the results from this study could be useful for public health officers to develop a system to monitor and prevent diarrhea outbreaks.

METHODS

The objective of this study was to analyse the epidemic outbreak patterns of diarrhea in Chiang Mai province, Northern Thailand, in terms of their geographical distributions and hotspot identification. The data of patients with diarrhea at village level and the 2001-2006 population censuses were collected to achieve the objective. Spatial analysis, using geographic information systems (GIS) and other methods, was used to uncover the hidden phenomena from the data. In the data analysis section, spatial statistics such as quadrant analysis (QA), nearest neighbour analysis (NNA), and spatial autocorrelation analysis (SAA), were used to identify the spatial patterns of diarrhea in Chiang Mai province. In addition, local indicators of spatial association (LISA) and kernel density (KD) estimation were used to detect diarrhea hotspots using data at village level.

RESULTS

The hotspot maps produced by the LISA and KD techniques showed spatial trend patterns of diarrhea diffusion. Villages in the middle and northern regions revealed higher incidences. Also, the spatial patterns of diarrhea during the years 2001 and 2006 were found to represent spatially clustered patterns, both at global and local scales.

CONCLUSION

Spatial analysis methods in GIS revealed the spatial patterns and hotspots of diarrhea in Chiang Mai province from the year 2001 to 2006. To implement specific and geographically appropriate public health risk-reduction programs, the use of such spatial analysis tools may become an integral component in the epidemiologic description, analysis, and risk assessment of diarrhea.