The application of geographical information systems to important public health problems in Africa

Health system assessment for access to care after injury in low- or middle-income countries: A mixed methods study from Northern Malawi

BACKGROUND

Injuries represent a vast and relatively neglected burden of disease affecting low- and middle-income countries (LMICs). While many health systems underperform in treating injured patients, most assessments have not considered the whole system. We integrated findings from 9 methods using a 3 delays approach (delays in seeking, reaching, or receiving care) to prioritise important trauma care health system barriers in Karonga, Northern Malawi, and exemplify a holistic health system assessment approach applicable in comparable settings.

METHODS AND FINDINGS

To provide multiple perspectives on each conceptual delay and include data from community-based and facility-based sources, we used 9 methods to examine the injury care health system. The methods were (1) household survey; (2) verbal autopsy analysis; (3) community focus group discussions (FGDs); (4) community photovoice; (5) facility care-pathway process mapping and elucidation of barriers following injury; (6) facility healthcare worker survey; (7) facility assessment survey; (8) clinical vignettes for care process quality assessment of facility-based healthcare workers; and (9) geographic information system (GIS) analysis. Empirical data collection took place in Karonga, Northern Malawi, between July 2019 and February 2020. We used a convergent parallel study design concurrently conducting all data collection before subsequently integrating results for interpretation. For each delay, a matrix was created to juxtapose method-specific data relevant to each barrier identified as driving delays to injury care. Using a consensus approach, we graded the evidence from each method as to whether an identified barrier was important within the health system. We identified 26 barriers to access timely quality injury care evidenced by at least 3 of the 9 study methods. There were 10 barriers at delay 1, 6 at delay 2, and 10 at delay 3. We found that the barriers "cost," "transport," and "physical resources" had the most methods providing strong evidence they were important health system barriers within delays 1 (seeking care), 2 (reaching care), and 3 (receiving care), respectively. Facility process mapping provided evidence for the greatest number of barriers-25 of 26 within the integrated analysis. There were some barriers with notable divergent findings between the community- and facility-based methods, as well as among different community- and facility-based methods, which are discussed. The main limitation of our study is that the framework for grading evidence strength for important health system barriers across the 9 studies was done by author-derived consensus; other researchers might have created a different framework.

CONCLUSIONS

By integrating 9 different methods, including qualitative, quantitative, community-, patient-, and healthcare worker-derived data sources, we gained a rich insight into the functioning of this health system's ability to provide injury care. This approach allowed more holistic appraisal of this health system's issues by establishing convergence of evidence across the diverse methods used that the barriers of cost, transport, and physical resources were the most important health system barriers driving delays to seeking, reaching, and receiving injury care, respectively. This offers direction and confidence, over and above that derived from single methodology studies, for prioritising barriers to address through health service development and policy.

The promise of data science for health research in Africa

Data science health research promises tremendous benefits for African populations, but its implementation is fraught with substantial ethical governance risks that could thwart the delivery of these anticipated benefits. We discuss emerging efforts to build ethical governance frameworks for data science health research in Africa and the opportunities to advance these through investments by African governments and institutions, international funding organizations and collaborations for research and capacity development.

Insecticide-treated bed net use and associated factors among households having under-five children in East Africa: a multilevel binary logistic regression analysis

BACKGROUND

Even though malaria is preventable, it remains the leading cause of under-five morbidity and mortality in low-and middle-income countries. Despite the World Health Organization (WHO) recommendations, its advantage, and its free-of-cost access, the utilization of insecticide-treated nets (ITN) is still low in East Africa. Therefore, this study aimed to assess ITN use and associated factors among households having under-five children in East Africa.

METHODS

The most recent Demographic and Health Survey (DHS) datasets of East African countries were used. A total of 174,411 weighted samples was used for analysis. Given the hierarchical nature of DHS data, a multilevel binary logistic regression model was fitted to identify factors associated with ITN use. Four models were fitted and a model with the lowest deviance value was chosen as the best-fitted model for the data. Variables with a p-value < 0.2 in the bivariable analysis were considered for the multivariable analysis. In the multivariable multilevel binary logistic regression analysis, the Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) was reported to declare the statistical significance and strength of association.

RESULTS

In this study, the proportion of ITN use among households having under-five children in East Africa was 46.32% (95% CI 46.08%, 46.55%), ranging from 11.8% in Zimbabwe to 70.03% in Rwanda. In the multivariable analysis, being in the age group 25-34 years, married, widowed, and divorced, primary and post-primary education, wealthy households, having a lower household size, many under-five children, having media exposure, and male-headed households were associated with higher odds of ITN use. Moreover, respondents from a rural place of residence, communities with a higher level of media exposure, communities with lower poverty levels, and communities with higher education levels had higher odds of ITN use.

CONCLUSION

In this study, the proportion of ITN use was relatively low. Both individual and community-level factors were associated with ITN use. Therefore, giving attention, especially to those who had no formal education, the poor, younger age groups, and households with the large family size is advisable to increase awareness about ITN use. Moreover, media campaigns regarding ITN use should be strengthened.

Access to care following injury in Northern Malawi, a comparison of travel time estimates between Geographic Information System and community household reports

INTRODUCTION

Injuries disproportionately impact low- and middle-income countries like Malawi. The Lancet Commission on Global Surgery's indicators include the population proportion accessing laparotomy and open fracture care, key trauma interventions, within two hours. The "Golden Hour" for receiving facility-based resuscitation also guides injury care system strengthening. Firstly, we estimated the proportion of the local population able to reach primary, secondary and tertiary facility care within two and one hours using Geographic Information System (GIS) analysis. Secondly, we compared community household-reported with GIS-estimated travel time.

METHODS

Using information from a Health and Demographic Surveillance Site (Karonga, Malawi) on road network, facility location, and local staff-estimated travel speeds, we used a GIS-generated friction surface to calculate the shortest travel time from all households to each facility serving the population. We surveyed community households who reported travel time to their preferred, closest, government secondary and tertiary facilities. For recently injured community members, time to reach facility care was recorded. To assess the relationship between community household-reported travel time and GIS-estimated travel time, we used linear regression to generate a proportionality constant. To assess associations and agreement between injured patient-reported and GIS-estimated travel time, we used Kendall rank and Cohen's kappa tests.

RESULTS

Using GIS, we estimated 79.1% of households could reach any secondary facility, 20.5% the government secondary facility, and 0% the government tertiary facility, within two hours. Only 28.2% could reach any secondary facility within one hour, 0% for the government secondary facility. Community household-reported travel time exceeded GIS-estimated travel time. The proportionality constant was 1.25 (95%CI 1.21-1.30) for the closest facility, 1.28 (95%CI 1.23-1.34) for the preferred facility, 1.45 (95%CI 1.33-1.58) for the government secondary facility, and 2.12 (95%CI 1.84-2.41) for tertiary care. Comparing injured patient-reported with GIS-estimated travel time, the correlation coefficient was 0.25 (SE 0.047) and Cohen's kappa was 0.15 (95%CI 0.078-0.23), suggesting poor agreement.

DISCUSSION

Most households couldn't reach government secondary care within recognised thresholds indicating poor temporal access. Since GIS-estimated travel time was shorter than community-reported travel time, the true proportion may be lower still. GIS derived estimates of population emergency care access in similar contexts should be interpreted accordingly.

Epidemiology incidence and geographical distribution of leptospirosis using GIS and its incidence prediction in Iran in 2021

Background: Leptospirosis is known as a public health problem in developing and developed countries. The aim of this study was to investigate the incidence and geographical distribution of leptospirosis using the Geographic Information System (GIS) and to predict its incidence in Iran in 2021.

Methods: This was a descriptive analytical study. Information on leptospirosis was obtained from the Center for Communicable Diseases Control during 2009-2015. In the next step, The ArcGIS 9.3 was used to prepare geographic maps of the disease incidence and frequency. Therefore, using the Raster Calculator tool, the disease prediction map was drawn.

Results: The results showed that the highest incidence of leptospirosis during 2009-2015 was observed in Gilan, Mazandaran, and Golestan provinces, respectively. The incidence of the disease had an increasing trend from 2013 to 2015. Based on the results of the modeling in Iran, the provinces of Gilan, Mazandaran, and Golestan, with 72.18%, 8.54%, and 4.95% of their area, respectively, have the largest areas at a high-risk for leptospirosis in the coming years.

Conclusion: The prevalence of leptospirosis is affected by geographical and climatic conditions of every region; thus, the incidence of the disease is higher in the provinces located at the Caspian coastal side and in some regions in Semnan province. Hence, if health authorities pay more attention to developing health plans to prevent the disease, the risk of disease in these areas will be reduced in the future.

Epidemiology incidence and geographical distribution of Meningitis using GIS and its incidence prediction in Iran in 2021

Background: Meningitis is classified as a medical emergency where the identification and early treatment of bacterial meningitis can eliminate serious consequences, such as hearing loss, memory problems, learning disabilities, brain damage, seizures, and death. The purpose of this study was to investigate the incidence and geographical distribution of meningitis using Geographic Information system (GIS) and to predict its incidence in Iran in 2021.

Methods: This was a descriptive analytical study. Information on pertussis was obtained from the Center for Communicable Diseases Control during 2010-2015. In the next step, ArcGIS 9.3 was used to prepare geographic maps of the disease incidence and frequency. Then, the disease prediction map was drawn using the Raster Calculator tool.

Results: The results showed that the highest incidence of meningitis during 2010-2015 was in Qazvin, Qom, and Kurdistan provinces. The incidence of meningitis in Iran increased from 9.77 in 2010 to 10.33 in 2015. Based on the modeling results for Iran, Qom, Qazvin, Kurdistan, Hamadan, and Mazandaran provinces with 78.89%, 74.68%, 70.07%, 43.97%, and 22.93% of their areas (Km²) are at high risk for meningitis in the coming years, respectively.

Conclusion: According to the results of this study, it can be concluded that Qom, Qazvin, Kurdistan, Hamedan, and Mazandaran provinces are at risk of the disease. Monitoring vaccination in high-risk groups can partially prevent the incidence of the disease in these areas.

Using Prospective Methods to Identify Fieldwork Locations Favourable to Understanding Divergences in Health Care Accessibility

Central to this article is the issue of choosing sites for where a fieldwork could provide a better understanding of divergences in health care accessibility. Access to health care is critical to good health, but inhabitants may experience barriers to health care limiting their ability to obtain the care they need. Most inhabitants of low-income countries need to walk long distances along meandering paths to get to health care services. Individuals in Malawi responded to a survey with a battery of questions on perceived difficulties in accessing health care services. Using both vertical and horizontal impedance, we modelled walking time between household locations for the individuals in our sample and the health care centres they were using. The digital elevation model and Tobler’s hiking function were used to represent vertical impedance, while OpenStreetMap integrated with land cover map were used to represent horizontal impedance. Combining measures of walking time and perceived accessibility in Malawi, we used spatial statistics and found spatial clusters with substantial discrepancies in health care accessibility, which represented fieldwork locations favourable for providing a better understanding of barriers to health access.

Stable and Local Reservoirs of Mycobacterium ulcerans Inferred from the Nonrandom Distribution of Bacterial Genotypes, Benin

Mycobacterium ulcerans is the causative agent of Buruli ulcer, a neglected tropical disease found in rural areas of West and Central Africa. Despite the ongoing efforts to tackle Buruli ulcer epidemics, the environmental reservoir of its pathogen remains elusive, underscoring the need for new approaches to improving disease prevention and management. In our study, we implemented a local-scale spatial clustering model and deciphered the genetic diversity of the bacteria in a small area of Benin where Buruli ulcer is endemic. Using 179 strain samples from West Africa, we conducted a phylogeographic analysis combining whole-genome sequencing with spatial scan statistics. The 8 distinct genotypes we identified were by no means randomly spread over the studied area. Instead, they were divided into 3 different geographic clusters, associated with landscape characteristics. Our results highlight the ability of M. ulcerans to evolve independently and differentially depending on location in a specific ecologic reservoir.

Geographical distribution of Typhoid using Geographic Information System (GIS) during 2009-2014 in Iran

Background: Salmonella induced infections remain one of the most important health problems worldwide. The purpose of this study is to investigate the incidence and geographical distribution of typhoid using GIS and to predict its incidence in Iran in 2021.

Methods: This study is a descriptive analytical study. Information on pertussis was obtained from the Center for Communicable Diseases Control during 2009-2015. In the next step, ArcGIS 9.3 was used to prepare geographic maps of the disease incidence and frequency Therefore, using the Raster Calculator tool, the disease prediction map was drawn.

Results: The results showed that the highest incidence of typhoid during 2009-2014 was in Kermanshah, Lorestan, Hamadan, Kurdistan, and Ilam provinces. The incidence of typhoid in Iran increased during 2009-2010. The annual incidence of typhoid decreased from 0.85 per 100,000 in 2010 to 0.5 in 2014. Based on the modeling results for Iran, Kermanshah, Lorestan, Kurdistan, Ilam and Hamadan provinces with 92.17%, 46.56%, 31.74%, 25.62% and 22.96% of their areas (Km2) are at high risk for typhoid in the coming years, respectively.

Conclusion: Considering that the provinces of Kermanshah, Lorestan, Kurdistan, Ilam, and Hamadan are at risk of typhoid incidence in the coming years in Iran, and given that salmonella infections have a direct relationship with the individual’s health status and individual’s environmental health and socioeconomic status, improving the health status and disease control in carriers as well as improving the socio-economic status of the population living in these areas can prevent the disease in the years to come.

Impact of a community-based intervention on Aedes aegypti and its spatial distribution in Ouagadougou, Burkina Faso

Background

Several studies highlighted the impact of community-based interventions whose purpose was to reduce the vectors’ breeding sites. These strategies are particularly interesting in low-and-middle-income countries which may find it difficult to sustainably assume the cost of insecticide-based interventions. In this case study we determine the spatial distribution of a community-based intervention for dengue vector control using different entomological indices. The objective was to evaluate locally where the intervention was most effective, using spatial analysis methods that are too often neglected in impact assessments.

Methods

Two neighbourhoods, Tampouy and Juvenat in Ouagadougou, Burkina Faso, were chosen among five after a survey was conducted, as part of an assessment related to the burden of dengue. As part of the community-based intervention conducted in Tampouy between August and early October 2016, an entomological survey was implemented in two phases. The first phase consisted of a baseline entomological characterization of potential breeding sites in the neighbourhood of Tampouy as well as in Juvenat, the control area. This phase was conducted in October 2015 at the end of the rainy season. The mosquito breeding sites were screened in randomly selected houses: 206 in Tampouy and 203 in Juvenat. A second phase took place after the intervention, in October 2016. The mosquito breeding sites were investigated in the same yards as during the baseline phase. We performed several entomological analyses to measure site productivity as well as before and after analysis using multilevel linear regression. We used Local Indicators of Spatial Association (LISAs) to analyse spatial concentrations of larvae.

Results

After the intervention, it is noted that LISAs at Tampouy reveal few aggregates of all types and the suppression of those existing before the intervention. The analysis therefore reveals that the intervention made it possible to reduce the number of concentration areas of high and low values of pupae.

Conclusions

The contribution of spatial methods for assessing community-based intervention are relevant for monitoring at local levels as a complement to epidemiological analyses conducted within neighbourhoods. They are useful, therefore, not only for assessment but also for establishing interventions. This study shows that spatial analyses also have their place in population health intervention research.

Understanding the determinants of GIT post-adoption: perspectives from Mozambican institutions

This study aims to understand the determinants of geographical information technologies at the scale of post-adoption use and intention to increase the level of use in Mozambican institutions. Three known theories (diffusion of innovation theory, technology - organisation - environment framework, and institutional theory) have been used in order to accomplish the study. The data analysis showed that the variables compatibility, geographical scope, expansion opportunities, and normative pressure contribute to explaining GIT use. Relative advantage, complexity, coercive pressure, and mimetic pressure contribute to explaining the intention to increase GIT levels of use. The model revealed substantial power of explanation for GIT post-adoption.

A Comparative Study of Spatial Distribution of Gastrointestinal Cancers in Poverty and Affluent Strata (Kermanshah Metropolis, Iran)

INTRODUCTION

The trend of cancers has witnessed a twofold rise in the last three decades, which is expected to be fivefold by 2030. On the other hand, gastrointestinal cancers have turned into one of the health issues in many societies. Given the presence of gastrointestinal cancer hot spots and evidence of health inequalities across Kermanshah Metropolis and the results of studies signaling the association between gastrointestinal cancers and socioeconomic status of individuals as well as evidence of unequal socioeconomic opportunities in this metropolis, the present study aimed to investigate the spatial distribution of gastrointestinal cancers in the poverty and affluent strata of Kermanshah Metropolis, Iran.

MATERIALS AND METHODS

In this descriptive-analytical study, the recorded data of patients, suffering from gastrointestinal cancers, in Kermanshah-based Pathology Centers and Vice Chancellery of Kermanshah University of Medical Sciences (2007-2012) were used. Moreover, to examine the status of gastrointestinal cancers in socioeconomic classes based on the census data collected during 2007-2012, 33 social, cultural, and structural indexes were extracted from the statistical blocks. Additionally, for data analysis and factor analysis, Kruskal-Wallis Test in the environment of SPSS and kernel density estimation (KDE) and Moran's I tests in the GIS environment were employed.

FINDINGS

The results of the present study revealed that the distribution of poverty (Z score = 48.916518, p value = 0.000000) and affluent strata (Z score = 14.345028, p value = 0.000000) followed clustered patterns (p < 0.01). Additionally, the results indicated that the spatial distribution pattern of the upper gastrointestinal cancer was clustered (Z score = 1.896996, p value = 0.007828), whereas the spatial distribution pattern of the lower gastrointestinal cancer was inclined to a randomized clustered pattern (Z score = 1.338121, p value = 0.000857) (p < 0.01). Finally, seven main hot spots were identified from the poverty stratum in Kermanshah, which perfectly overlapped the hot spots of upper gastrointestinal cancer. Similarly, four main hot spots were identified from the affluent stratum in Kermanshah, which overlapped the hot spots of lower gastrointestinal cancer. The results of the Kruskal-Wallis Test demonstrated that the poverty and affluent strata were significantly different from each other in terms of gastrointestinal cancer: upper gastrointestinal cancer (p < 0.05 and X²=10.064) and lower gastrointestinal cancer (p < 0.05 and X²=10.253).

CONCLUSION

The results of the present study showed that the ratio of patients with lower gastrointestinal cancers was higher than the incidence of upper gastrointestinal cancers over the 5-year period under study. Moreover, in Kermanshah Metropolis, there was a significant difference between the upper gastrointestinal cancer in the poverty stratum and the lower gastrointestinal cancer in the affluent stratum. Hence, it is suggested that GIS be applied as a tool for identifying the patterns of effective factors of this type of cancer in each social class, and it is recommended that some effective policies be presented and adopted by health managers according to the role and importance of socioeconomic, environmental, and nutritional factors in the poverty and affluent strata of society, and people at risk be equipped with preventive training programs in this respect.

Spatial distribution and characteristics of HIV clusters in Ethiopia

OBJECTIVES

Ethiopia's HIV prevalence has decreased by 75% in the past 20 years with the implementation of antiretroviral therapy, but HIV transmission continues in high-risk clusters. Identifying the spatial and temporal trends, and epidemiologic correlates, of these clusters can lead to targeted interventions.

METHODS

We used biomarker and survey data from the 2005, 2011 and 2016 Ethiopia Demographic and Health Surveys (DHS). The spatial-temporal distribution of HIV was estimated using the Kulldorff spatial scan statistic, a likelihood-based method for determining clustering. Significant clusters (P < 0.05) were identified and compared based on HIV risk factors to non-cluster areas.

RESULTS

In 2005, 2011 and 2016, respectively, 219, 568 and 408 individuals tested positive for HIV. Four HIV clusters were identified, representing 17% of the total population and 43% of all HIV cases. The clusters were centred around Addis Ababa (1), Afar (2), Dire Dawa (3) and Gambella (4). Cluster 1 had higher rates of unsafe injections (4.9% vs. 2.2%, P < 0.001) and transactional sex (6.0% vs. 1.6%, P < 0.001) than non-cluster regions, but more male circumcision (98.5% vs. 91.3%, P < 0.001). Cluster 2 had higher levels of transactional sex (4.9% vs. 1.6%, P < 0.01), but lower levels of unsafe injections (0.8% vs. 2.2%, P < 0.01). Cluster 3 had fewer individuals with> 1 sexual partner (0% vs. 1.7%, P < 0.001) and more male circumcision (100% vs. 91.3%, P < 0.001). Cluster 4 had less male circumcision (59.1% vs. 91.3%, P < 0.01).

CONCLUSIONS

In Ethiopia, geographic HIV clusters are driven by different risk factors. Decreasing the HIV burden requires targeted interventions.

Clustering and spatial heterogeneity of bovine tuberculosis at the livestock/wildlife interface areas in Namwala District of Zambia

BACKGROUND AND AIM

Bovine tuberculosis (bTB) remains a major public health issue in Zambia and has been exacerbated by human immunodeficiency virus prevalence and consumption of unpasteurized milk in the Southern Province of the country. The prevalence of bTB has been established to be linked to Kafue Lechwe, which act as reservoir hosts and share grazing fields with domestic cattle. No studies have so far used geographic information system (GIS) to investigate the relationship between the reservoir hosts (Kafue Lechwe) and domestic animals. This study, therefore, aimed to apply GIS to investigate the spatial distribution of bTB in Namwala District of the Southern Province of the country.

MATERIALS AND METHODS

To investigate the spatial distribution of bTB, geographical positioning system (GPS) coordinates representing 96 cattle herds across 20 independent villages were captured alongside risk factor data. The 96 herds were based on abattoir reports of condemned carcasses and a trace back. Positive herds were confirmed by cross-reference to purified protein derivative tests conducted by the District Veterinary Office. The GPS coordinates were transferred into ArcView 3.2 and laid on the map of Namwala District alongside physical features, including national parks, game management areas, and flood plains. Questionnaires were administered across 96 independent households to assess risk factors of bTB transmission.

RESULTS

The results revealed a "clustered" spatial distribution of the disease in cattle in Namwala District of Zambia, particularly significant in the eastern interface areas of the district (p=0.006 using Moran's I). Abattoir to production area trace back revealed a herd-level prevalence of 36.4% (95% CI=26.7-46.3%) among cattle herds in Namwala District, whereas individual animal prevalence ranged from 0% to 14% (95% CI=2.4-26.2%). Further, GPS data indicated that the majority of the positive herds were located at the livestock/wildlife interface area. Contacts with wildlife, coupled with sharing grazing, and watering points were found to be significant risk factors for bTB transmission.

CONCLUSION

This study demonstrated the presence of bTB in cattle and associated spatial risk factors. In particular, bTB was observed to be a function of animal location within the livestock/wildlife interface area. GIS is thus an applicable and important tool in studying disease distribution.

Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled geographical access to maternal care in Mozambique, India and Pakistan

BACKGROUND

Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled access predicts fairly the vulnerability in women seeking maternal care across different spatial settings.

OBJECTIVES

This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility.

METHODS

Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland-Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used.

RESULTS

Modelled geographical access (P) is generally lower than self-reported access (R), but there is a geography to this relationship. In India and Pakistan, potential access (P) compared fairly with self-reported travel times (R) [P (H₀: Mean difference = 0)] < .001, limits of agreement: [- 273.81; 56.40] and [- 264.10; 94.25] respectively. In Mozambique, mean differences between the two measures of access were significantly different from 0 [P (H₀: Mean difference = 0) = 0.31, limits of agreement: [- 187.26; 199.96]].

CONCLUSION

Modelling access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling access should not be viewed through a geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494.

Spatial Distribution of HIV Prevalence among Young People in Mozambique

Mozambique has a high burden of HIV and is currently ranked sixth worldwide for adult prevalence. In Mozambique, HIV prevalence is not uniformly distributed geographically and throughout the population. We investigated the spatial distribution of HIV infection among adolescents and young people in Mozambique using the 2009 AIDS Indicator Survey (AIS). Generalized geoadditive modeling, combining kriging and additive modeling, was used to study the geographical variability of HIV risk among young people. The nonlinear spatial effect was assessed through radial basis splines. The estimation process was done using two-stage iterative penalized quasi-likelihood within the framework of a mixed-effects model. Our estimation procedure is an extension of the approach by Vandendijck et al., estimating the range (spatial decay) parameter in a binary context. The results revealed the presence of spatial patterns of HIV infection. After controlling for important covariates, the results showed a greater burden of HIV/AIDS in the central and northern regions of the country. Several socio-demographic, biological, and behavioral factors were found to be significantly associated with HIV infection among young people. The findings are important, as they can help health officials and policy makers to design targeted interventions for responding to the HIV epidemic.

Spatial Distribution of Cutaneous Leishmaniasis Cases Referred to Health Centers of Three Khorasan Provinces in Iran Using Geographical Information System

BACKGROUND

Nowadays, geographic information system (GIS) is one of the most useful epidemiological tools for identifying high-risk areas of cutaneous leishmaniasis. The aim of this study was to determine the spatial distribution of cutaneous leishmaniasis in northeastern Iran.

METHODS

In this cross-sectional study, information on positive cases of cutaneous leishmaniasis in the three provinces located in northeastern Iran during Jul 2011 to Jul 2017 was obtained from the Iranian Ministry of Health. Based on the postal address of each case, the geographical coordinates of each patient were determined for spatial analysis of cutaneous leishmaniasis. For spatial analysis, Moran's index autocorrelation and Kriging interpolation method were used in GIS software.

RESULTS

Moran's index autocorrelation showed that spatial distribution of disease incidence in the study area was cluster pattern (Z-score > 1). In addition, Kriging interpolation method revealed that 90% of southern parts of North Khorasan province and northern parts of Razavi Khorasan Province formed hot spots.

CONCLUSION

The CL incidence is a function of spatial and geographical trends. In addition, spatial trends in the disease incidence distribution indicate that it is not greatly increased or decreased from one area to another. It appears as hot spots areas. Spatial analysis by showing high risk areas can be useful tools for controlling and preventing CL incidence.

Strengthening acute flaccid paralysis surveillance post Ebola virus disease outbreak 2015 - 2017: the Liberia experience

Introduction

Liberia remains at high risk of poliovirus outbreaks due to importation. The country maintained certification level acute flaccid paralysis (AFP) surveillance indicators each year until 2014 due to Ebola outbreak. During this time, there was a significant drop in non-polio AFP rate to (1.2/100,000 population under 15 years) in 2015 from 2.9/100, 000 population in 2013, due to a variety of reasons including suspension on shipment of acute flaccid paralysis stool specimen to the polio regional lab in Abidjan, refocusing of surveillance officers attention solely on Ebola virus disease (EVD) surveillance, inactivation of national polio expert committee (NPEC) and National Certification Committee (NCC). The Ministry of Health (MOH) supported by partners worked to restore AFP surveillance post EVD outbreak and ensure that Liberia maintains its polio free certification.

Methods

We conducted a desk review to summarize key activities conducted to restore acute flaccid paralysis (AFP) surveillance based on World Health Organization (WHO) AFP surveillance guidelines for Africa region. We also reviewed AFP surveillance indicators and introduction of new technologies. Data sources were from program reports, scientific and gray literature, AFP database, auto visual AFP detection and reporting (AVADAR) and ONA Servers. Data analysis was done using Microsoft excel and access spread sheets, ONA software and Geographic Information System (Arc GIS).

Results

AFP surveillance indicators improved with a rebound of non-polio AFP rate (NPAFP) rate from 1.2/100, 000 population under 15 years in 2015 to 4.3 in 2017. The stool adequacy rate at the national level also improved from 79% in 2016 to 82% in 2017, meeting the global target. The percentage of counties meeting the two critical AFP surveillance indicators NPAFP rate and stool adequacy improved from 47% in 2016 to 67% in 2017.The Last polio case reported in Liberia was in late 2010.

Conclusion

There was significant improvement in the key AFP surveillance indicators such as NPAFP rate and stool adequacy with a 3.5 fold increase in NPAFP from 2014 to 2017. By 2017, the stool adequacy rate was up to target levels compared to 2016, which was below target level of 80%. The number of counties meeting target for the two critical AFP surveillance indicators also increased by 20% points between 2016 and 2017. Similarly there was approximately two-fold increase in the oral polio vaccines (OPV) coverage for the reported AFP cases between 2015 and 2017. Strategies employed to address gaps in AFP surveillance included enhanced active case search for AFP, re-instatement of laboratory testing, supportive supervision in addition to facilitating enhanced community engagement in surveillance activities. New technologies such as AVADAR Pilot, electronic integrated supportive supervision (ISS) and electronic surveillance (eSurv) tools were introduced to improve real time AFP case reporting. However, there remain residual gaps in AFP surveillance in the country especially at the sub-national level. Similarly, the newly introduced technologies will require continued funding and capacity building for MOH staff to ensure sustainability of the initiatives.

Geographic Information Systems, spatial analysis, and HIV in Africa: A scoping review

INTRODUCTION

Geographic Information Systems (GIS) and spatial analysis are emerging tools for global health, but it is unclear to what extent they have been applied to HIV research in Africa. To help inform researchers and program implementers, this scoping review documents the range and depth of published HIV-related GIS and spatial analysis research studies conducted in Africa.

METHODS

A systematic literature search for articles related to GIS and spatial analysis was conducted through PubMed, EMBASE, and Web of Science databases. Using pre-specified inclusion criteria, articles were screened and key data were abstracted. Grounded, inductive analysis was conducted to organize studies into meaningful thematic areas.

RESULTS AND DISCUSSION

The search returned 773 unique articles, of which 65 were included in the final review. 15 different countries were represented. Over half of the included studies were published after 2014. Articles were categorized into the following non-mutually exclusive themes: (a) HIV geography, (b) HIV risk factors, and (c) HIV service implementation. Studies demonstrated a broad range of GIS and spatial analysis applications including characterizing geographic distribution of HIV, evaluating risk factors for HIV, and assessing and improving access to HIV care services.

CONCLUSIONS

GIS and spatial analysis have been widely applied to HIV-related research in Africa. The current literature reveals a diversity of themes and methodologies and a relatively young, but rapidly growing, evidence base.

Exploring the spatial relationship between primary road distance to antenatal clinics and HIV prevalence in pregnant females of Lilongwe, Malawi

While urbanization in a sub-Saharan African (SSA) context can lead to greater independence in women, various sociological, biological, and geographical factors in urban areas may keep women at a higher risk for HIV than men. Access to major roads during Malawi's transition into rapid urbanization may leave women disproportionately vulnerable to HIV infection. It is not well established whether women who report to health clinics closer to major roads have higher or lower levels of HIV. In this study we explored the spatial heterogeneity of HIV prevalence among pregnant females in Lilongwe District, Malawi. Using Geographic Information Systems, we visually represented patterns of HIV prevalence in relation to primary roads. HIV prevalence data for 2015 were obtained from 44 antenatal clinics (ANC) in Lilongwe District. ANC prevalence data were aggregated to the administrative area and mapped. Euclidean distance between clinics and two primary roads that run through Lilongwe District were measured. A correlation was run to assess the relationship between area-level ANC HIV prevalence and clinic distance to the nearest primary road. ANC HIV prevalence ranged from 0% to 10.3%. Clinic to major road distance ranged from 0.1 to 35 km. Correlation results ( r= -0.622, p = 0.002) revealed a significant negative relationship between clinic distance to primary road and HIV prevalence, indicating that the farther the clinics stood from primary roads, the lower the reported antenatal HIV prevalence. Overall, the clinic catchments through which the major roads run reported higher ANC HIV prevalence. Antenatal HIV prevalence decreases as ANC distance from primary roads increases in Lilongwe, Malawi. As urbanization continues to grow in this region, road distance may serve as a good indicator of HIV burden and help to guide targeted prevention and treatment efforts.

Spatio-temporal distribution analysis of zoonotic cutaneous leishmaniasis in Qom Province, Iran

Geographic information system (GIS) nowadays is one of the most helpful epidemiological tools for identifying the high risk areas of cutaneous leishmaniasis (CL). This study was conducted to determine the spatio-temporal distribution of CL in Qom province during 2009-2017. In a cross-sectional study, for the survey of spatial dispersion of CL in the study region, the incidence rate of disease was calculated in all of 23 villages during 2009-2017. Then, spatial analysis of the infection was performed using two methods: spatial autocorrelation (Moran's I) in order to determine the special distribution pattern of disease and Kriging method to reveal high risk areas for disease. The incidence of CL in Qom province has been decreasing as of 2009-2015 and increasing in 2015-2017. The highest incidence was stated in 2009 (36.5 per 100,000) and the least was reported in 2015 (13.3 per 100,000). The Moran autocorrelation index revealed that the study area has a cluster pattern. The temporal distribution of disease incidence showed that northeast, southwest and northwest parts of Qom province involved highest incidence of CL in 90% significant level. Leishmaniasis incidence is a function of spatial and geographical trends, thus spatial variations of the infection incidence illustrate that the incidence rate does not increase or decrease from one region to another intensively. The results of this study indicate that marking high risk areas using spatial analysis can be helpful as a main tool in CL control and prevention.

Establishing a Demographic, Development and Environmental Geospatial Surveillance Platform in India: Planning and Implementation

BACKGROUND

Inadequate administrative health data, suboptimal public health infrastructure, rapid and unplanned urbanization, environmental degradation, and poor penetration of information technology make the tracking of health and well-being of populations and their social determinants in the developing countries challenging. Technology-integrated comprehensive surveillance platforms have the potential to overcome these gaps.

OBJECTIVE

This paper provides methodological insights into establishing a geographic information system (GIS)-integrated, comprehensive surveillance platform in rural North India, a resource-constrained setting.

METHODS

The International Clinical Epidemiology Network Trust International established a comprehensive SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in rural Palwal, a district in Haryana, North India. The surveillance platform evolved by adopting four major steps: (1) site preparation, (2) data construction, (3) data quality assurance, and (4) data update and maintenance system. Arc GIS 10.3 and QGIS 2.14 software were employed for geospatial data construction. Surveillance data architecture was built upon the geospatial land parcel datasets. Dedicated software (SOMAARTH-1) was developed for handling high volume of longitudinal datasets. The built infrastructure data pertaining to land use, water bodies, roads, railways, community trails, landmarks, water, sanitation and food environment, weather and air quality, and demographic characteristics were constructed in a relational manner.

RESULTS

The comprehensive surveillance platform encompassed a population of 0.2 million individuals residing in 51 villages over a land mass of 251.7 sq km having 32,662 households and 19,260 nonresidential features (cattle shed, shops, health, education, banking, religious institutions, etc). All land parcels were assigned georeferenced location identification numbers to enable space and time monitoring. Subdivision of villages into sectors helped identify socially homogenous community clusters (418/676, 61.8%, sectors). Water and hygiene parameters of the whole area were mapped on the GIS platform and quantified. Risk of physical exposure to harmful environment (poor water and sanitation indicators) was significantly associated with the caste of individual household (P=.001), and the path was mediated through the socioeconomic status and density of waste spots (liquid and solid) of the sector in which these households were located. Ground-truthing for ascertaining the land parcel level accuracies, community involvement in mapping exercise, and identification of small habitations not recorded in the administrative data were key learnings.

CONCLUSIONS

The SOMAARTH DDESS experience allowed us to document and explore dynamic relationships, associations, and pathways across multiple levels of the system (ie, individual, household, neighborhood, and village) through a geospatial interface. This could be used for characterization and monitoring of a wide range of proximal and distal determinants of health.

Towards universal health coverage: a mixed-method study mapping the development of the faith-based non-profit sector in the Ghanaian health system

BACKGROUND

Faith-based non-profit (FBNP) providers have had a long-standing role as non-state, non-profit providers in the Ghanaian health system. They have historically been considered to be important in addressing the inequitable geographical distribution of health services and towards the achievement of universal health coverage (UHC), but in changing contexts, this contribution is being questioned. However, any assessment of contribution is hampered by the lack of basic information about their comparative presence and coverage in the Ghanaian health system. In response, since the 1950s, there have been repeated calls for the 'mapping' of faith-based health assets.

METHODS

A historically-focused mixed-methods study was conducted, collecting qualitative and quantitative data and combining geospatial mapping with varied documentary resources (secondary and primary, current and archival). Geospatial maps were developed, providing a visual representation of changes in the spatial footprint of the Ghanaian FBNP health sector.

RESULTS

The geospatial maps show that FBNPs were originally located in rural remote areas of the country but that this service footprint has evolved over time, in line with changing social, political and economic contexts.

CONCLUSION

FBNPs have had a long-standing role in the provision of health services and remain a valuable asset within national health systems in Ghana and sub-Saharan Africa more broadly. Collaboration between the public sector and such non-state providers, drawing on the comparative strengths and resources of FBNPs and focusing on whole system strengthening, is essential for the achievement of UHC.

Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases

Background

HLA genes are the most polymorphic of the human genome and have distinct allelic frequencies in populations of different geographical regions of the world, serving as genetic markers in ancestry studies. In addition, specific HLA alleles may be associated with various autoimmune and infectious diseases. The bone marrow donor registry in Brazil is the third largest in the world, and it counts with genetic typing of HLA-A, -B, and -DRB1. Since 1991 Brazil has maintained the DATASUS database, a system fed with epidemiological and health data from compulsory registration throughout the country.

Methods

In this work, we perform spatial analysis and georeferencing of HLA genetic data from more than 86,000 bone marrow donors from Rio Grande do Sul (RS) and data of hospitalization for rheumatoid arthritis, multiple sclerosis and Crohn’s disease in RS, comprising the period from 1995 to 2016 obtained through the DATASUS system. The allele frequencies were georeferenced using Empirical Bayesian Kriging; the diseases prevalence were georeferenced using Inverse Distance Weighted and cluster analysis for both allele and disease were performed using Getis-Ord Gi* method. Spearman’s test was used to test the correlation between each allele and disease.

Results

The results indicate a HLA genetic structure compatible with the history of RS colonization, where it is possible to observe differentiation between regions that underwent different colonization processes. Spatial analyzes of autoimmune disease hospitalization data were performed revealing clusters for different regions of the state for each disease analyzed. The correlation test between allelic frequency and the occurrence of autoimmune diseases indicated a significant correlation between the HLA-B*08 allele and rheumatoid arthritis.

Conclusions

Genetic mapping of populations and the spatial analyzes such as those performed in this work have great economic relevance and can be very useful in the formulation of public health campaigns and policies, contributing to the planning and adjustment of clinical actions, as well as informing and educating professionals and the population.

Electronic supplementary material

The online version of this article (10.1186/s12942-018-0154-8) contains supplementary material, which is available to authorized users.

Combining survey data, GIS and qualitative interviews in the analysis of health service access for persons with disabilities

Background

Equitable access to health services is a key ingredient in reaching health for persons with disabilities and other vulnerable groups. So far, research on access to health services in low- and middle-income countries has largely relied on self-reported survey data. Realizing that there may be substantial discrepancies between perceived and actual access, other methods are needed for more precise knowledge to guide health policy and planning. The objective of this article is to describe and discuss an innovative methodological triangulation where statistical and spatial analysis of perceived distance and objective measures of access is combined with qualitative evidence.

Methods

The data for the study was drawn from a large household and individual questionnaire based survey carried out in Namibia and Malawi. The survey data was combined with spatial data of respondents and health facilities, key informant interviews and focus group discussions. To analyse access and barriers to access, a model is developed that takes into account both measured and perceived access. The geo-referenced survey data is used to establish four outcome categories of perceived and measured access as either good or poor. Combined with analyses of the terrain and the actual distance from where the respondents live to the health facility they go to, the data allows for categorising areas and respondents according to the four outcome categories. The four groups are subsequently analysed with respect to variation in individual characteristics and vulnerability factors. The qualitative component includes participatory map drawing and is used to gain further insight into the mechanisms behind the different combinations of perceived and actual access.

Results

Preliminary results show that there are substantial discrepancies between perceived and actual access to health services and the qualitative study provides insight into mechanisms behind such divergences.

Conclusion

The novel combination of survey data, geographical data and qualitative data will generate a model on access to health services in poor contexts that will feed into efforts to improve access for the most vulnerable people in underserved areas.

Spatial panorama of malaria prevalence in Africa under climate change and interventions scenarios

Background

Malaria is highly sensitive to climatic variables and is strongly influenced by the presence of vectors in a region that further contribute to parasite development and sustained disease transmission. Mathematical analysis of malaria transmission through the use and application of the value of the basic reproduction number (R₀) threshold is an important and useful tool for the understanding of disease patterns.

Methods

Temperature dependence aspect of R₀ obtained from dynamical mathematical network model was used to derive the spatial distribution maps for malaria transmission under different climatic and intervention scenarios. Model validation was conducted using MARA map and the Annual Plasmodium falciparum Entomological Inoculation Rates for Africa.

Results

The inclusion of the coupling between patches in dynamical model seems to have no effects on the estimate of the optimal temperature (about 25 °C) for malaria transmission. In patches environment, we were able to establish a threshold value (about α = 5) representing the ratio between the migration rates from one patch to another that has no effect on the magnitude of R₀. Such findings allow us to limit the production of the spatial distribution map of R₀ to a single patch model. Future projections using temperature changes indicated a shift in malaria transmission areas towards the southern and northern areas of Africa and the application of the interventions scenario yielded a considerable reduction in transmission within malaria endemic areas of the continent.

Conclusions

The approach employed here is a sole study that defined the limits of contemporary malaria transmission, using R₀ derived from a dynamical mathematical model. It has offered a unique prospect for measuring the impacts of interventions through simple manipulation of model parameters. Projections at scale provide options to visualize and query the results, when linked to the human population could potentially deliver adequate highlight on the number of individuals at risk of malaria infection across Africa. The findings provide a reasonable basis for understanding the fundamental effects of malaria control and could contribute towards disease elimination, which is considered as a challenge especially in the context of climate change.

Children who have received no routine polio vaccines in Nigeria: Who are they and where do they live?

Nigeria has made remarkable progress against polio, but 2 wild polio virus cases were reported in August 2016; putting an end to 2 y without reported cases. We examined the extent of geographical disparities in childhren not vaccinated against polio and examined individual- and community-level predictors of non-vaccination in Nigeria. We applied multilevel logistic regression models to the recent Nigeria Demographic and Health Survey. The percentage of children not routinely vaccinated against polio in Nigeria varied greatly and clustered geographically, mainly in north-eastern states, with a great risk of spread of transmission within these states and potential exportation to neighboring states and countries. Only about one-third had received all recommended 4 routine oral polio vaccine doses. Non-vaccinated children tended to have a mother who had no formal education and who was currently not working, live in poorer households and were from neighborhoods with higher maternal illiteracy rates.

Spatial methods for infectious disease outbreak investigations: systematic literature review

Investigations of infectious disease outbreaks are conventionally framed in terms of person, time and place. Although geographic information systems have increased the range of tools available, spatial analyses are used relatively infrequently. We conducted a systematic review of published reports of outbreak investigations worldwide to estimate the prevalence of spatial methods, describe the techniques applied and explore their utility. We identified 80 reports using spatial methods published between 1979 and 2013, ca 0.4% of the total number of published outbreaks. Environmental or waterborne infections were the most commonly investigated, and most reports were from the United Kingdom. A range of techniques were used, including simple dot maps, cluster analyses and modelling approaches. Spatial tools were usefully applied throughout investigations, from initial confirmation of the outbreak to describing and analysing cases and communicating findings. They provided valuable insights that led to public health actions, but there is scope for much wider implementation and development of new methods.

Role of spatial tools in public health policymaking of Bangladesh: opportunities and challenges

In spite of the increasing efforts to gather spatial data in developing countries, the use of maps is mostly for visualization of health indicators rather than informed decision-making. Various spatial tools can aid policymakers to allocate resources effectively, predict patterns in communicable or infectious diseases, and provide insights into geographical factors which are associated with utilization or adequacy of health services. In Bangladesh, the launch of District Health Information System 2, along with recent efforts to gather spatial data of facilities location, provides an interesting opportunity to study the current landscape and the potential barriers in advancing the use of spatial tools for informed decision making. This study assessed the current level of map usage and spatial tools for health sector planning in Bangladesh, focusing on investigating why map usage and spatial tools remained at a basic level for the purpose of health policy. The study design involved in-depth interviews, followed by an expert survey (n = 39) obtained through snowball sampling.Our survey revealed that assessing areas with shortage of community health workers emerged as the top most for basic map usage or primarily for visualization purpose, while planning for emergency and obstetric care services, and disease mapping was the most frequent category for intermediate and advanced map usage, respectively. Furthermore, we found lack of inter-institutional collaboration, lack of continuous availability of trained personnel, and lack of awareness on the use of geographic information system (GIS) as a decision-making tool as three most critical barriers in the current landscape. Our findings highlight the barriers in increasing the adoption of spatial tools for health policymaking and planning in Bangladesh.

Correlation Assessment of Climate and Geographic Distribution of Tuberculosis Using Geographical Information System (GIS)

BACKGROUND

Tuberculosis (TB) spread pattern is influenced by geographic and social factors. Nowadays Geographic Information System (GIS) is one of the most important epidemiological instrumentation identifying high-risk population groups and geographic areas of TB. The aim of this study was to determine the correlation between climate and geographic distribution of TB in Khuzestan Province using GIS during 2005-2012.

METHODS

Through an ecological study, all 6363 patients with definite diagnosis of TB from 2005 until the end of September 2012 in Khuzestan Province, southern Iran were diagnosed. Data were recorded using TB- Register software. Tuberculosis incidence based on the climate and the average of annual rain was evaluated using GIS. Data were analyzed through SPSS software. Independent t-test, ANOVA, Linear regression, Pearson and Eta correlation coefficient with a significance level of less than 5% were used for the statistical analysis.

RESULTS

The TB incidence was different in various geographic conditions. The highest mean of TB cumulative incidence rate was observed in extra dry areas (P= 0.017). There was a significant inverse correlation between annual rain rate and TB incidence rate (R= -0.45, P= 0.001). The lowest TB incidence rate (0-100 cases per 100,000) was in areas with the average of annual rain more than 1000 mm (P= 0.003).

CONCLUSION

The risk of TB has a strong relationship with climate and the average of annual rain, so that the risk of TB in areas with low annual rainfall and extra dry climate is more than other regions. Services and special cares to high-risk regions of TB are recommended.

How Can Childbirth Care for the Rural Poor Be Improved? A Contribution from Spatial Modelling in Rural Tanzania

Introduction

Maternal and perinatal mortality remain a challenge in resource-limited countries, particularly among the rural poor. To save lives at birth health facility delivery is recommended. However, increasing coverage of institutional deliveries may not translate into mortality reduction if shortage of qualified staff and lack of enabling working conditions affect quality of services. In Tanzania childbirth care is available in all facilities; yet maternal and newborn mortality are high. The study aimed to assess in a high facility density rural context whether a health system organization with fewer delivery sites is feasible in terms of population access.

Methods

Data on health facilities’ location, staffing and delivery caseload were examined in Ludewa and Iringa Districts, Southern Tanzania. Geospatial raster and network analysis were performed to estimate access to obstetric services in walking time. The present geographical accessibility was compared to a theoretical scenario with a 40% reduction of delivery sites.

Results

About half of first-line health facilities had insufficient staff to offer full-time obstetric services (45.7% in Iringa and 78.8% in Ludewa District). Yearly delivery caseload at first-line health facilities was low, with less than 100 deliveries in 48/70 and 43/52 facilities in Iringa and Ludewa District respectively. Wide geographical overlaps of facility catchment areas were observed. In Iringa 54% of the population was within 1-hour walking distance from the nearest facility and 87.8% within 2 hours, in Ludewa, the percentages were 39.9% and 82.3%. With a 40% reduction of delivery sites, approximately 80% of population will still be within 2 hours’ walking time.

Conclusions

Our findings from spatial modelling in a high facility density context indicate that reducing delivery sites by 40% will decrease population access within 2 hours by 7%. Focused efforts on fewer delivery sites might assist strengthening delivery services in resource-limited settings.

Leveraging community health worker system to map a mountainous rural district in low resource setting: a low-cost approach to expand use of geographic information systems for public health

Background

Geographic Information Systems (GIS) have become an important tool in monitoring and improving health services, particularly at local levels. However, GIS data are often unavailable in rural settings and village-level mapping is resource-intensive. This study describes the use of community health workers’ (CHW) supervisors to map villages in a mountainous rural district of Northern Rwanda and subsequent use of these data to map village-level variability in safe water availability.

Methods

We developed a low literacy and skills-focused training in the local language (Kinyarwanda) to train 86 CHW Supervisors and 25 nurses in charge of community health at the health center (HC) and health post (HP) levels to collect the geographic coordinates of the villages using Global Positioning Systems (GPS). Data were validated through meetings with key stakeholders at the sub-district and district levels and joined using ArcMap 10 Geo-processing tools. Costs were calculated using program budgets and activities’ records, and compared with the estimated costs of mapping using a separate, trained GIS team. To demonstrate the usefulness of this work, we mapped drinking water sources (DWS) from data collected by CHW supervisors from the chief of the village. DWSs were categorized as safe versus unsafe using World Health Organization definitions.

Result

Following training, each CHW Supervisor spent five days collecting data on the villages in their coverage area. Over 12 months, the CHW supervisors mapped the district’s 573 villages using 12 shared GPS devices. Sector maps were produced and distributed to local officials. The cost of mapping using CHW supervisors was $29,692, about two times less than the estimated cost of mapping using a trained and dedicated GIS team ($60,112). The availability of local mapping was able to rapidly identify village-level disparities in DWS, with lower access in populations living near to lakes and wetlands (p < .001).

Conclusion

Existing national CHW system can be leveraged to inexpensively and rapidly map villages even in mountainous rural areas. These data are important to provide managers and decision makers with local-level GIS data to rapidly identify variability in health and other related services to better target and evaluate interventions.

Methods to measure potential spatial access to delivery care in low- and middle-income countries: a case study in rural Ghana

BACKGROUND

Access to skilled attendance at childbirth is crucial to reduce maternal and newborn mortality. Several different measures of geographic access are used concurrently in public health research, with the assumption that sophisticated methods are generally better. Most of the evidence for this assumption comes from methodological comparisons in high-income countries. We compare different measures of travel impedance in a case study in Ghana's Brong Ahafo region to determine if straight-line distance can be an adequate proxy for access to delivery care in certain low- and middle-income country (LMIC) settings.

METHODS

We created a geospatial database, mapping population location in both compounds and village centroids, service locations for all health facilities offering delivery care, land-cover and a detailed road network. Six different measures were used to calculate travel impedance to health facilities (straight-line distance, network distance, network travel time and raster travel time, the latter two both mechanized and non-mechanized). The measures were compared using Spearman rank correlation coefficients, absolute differences, and the percentage of the same facilities identified as closest. We used logistic regression with robust standard errors to model the association of the different measures with health facility use for delivery in 9,306 births.

RESULTS

Non-mechanized measures were highly correlated with each other, and identified the same facilities as closest for approximately 80% of villages. Measures calculated from compounds identified the same closest facility as measures from village centroids for over 85% of births. For 90% of births, the aggregation error from using village centroids instead of compound locations was less than 35 minutes and less than 1.12 km. All non-mechanized measures showed an inverse association with facility use of similar magnitude, an approximately 67% reduction in odds of facility delivery per standard deviation increase in each measure (OR = 0.33).

CONCLUSION

Different data models and population locations produced comparable results in our case study, thus demonstrating that straight-line distance can be reasonably used as a proxy for potential spatial access in certain LMIC settings. The cost of obtaining individually geocoded population location and sophisticated measures of travel impedance should be weighed against the gain in accuracy.

Spatial analysis of factors associated with HIV infection among young people in Uganda, 2011

Background

The HIV epidemic in East Africa is of public health importance with an increasing number of young people getting infected. This study sought to identify spatial clusters and examine the geographical variation of HIV infection at a regional level while accounting for risk factors associated with HIV/AIDS among young people in Uganda.

Methods

A secondary data analysis was conducted on a survey cross-sectional design whose data were obtained from the 2011 Uganda Demographic and Health Survey (DHS) and AIDS Indicator Survey (AIS) for 7 518 young people aged 15-24 years. The analysis was performed in three stages while incorporating population survey sampling weights. Maximum likelihood-based logistic regression models were used to explore the non-spatially adjusted factors associated with HIV infection. Spatial scan statistic was used to identify geographical clusters of elevated HIV infections which justified modelling using a spatial random effects model by Bayesian-based logistic regression models.

Results

In this study, 309/533 HIV sero-positive female participants were selected with majority residing in the rural areas [386(72%)]. Compared to singles, those currently [Adjusted Odds Ratio (AOR) =3.64; (95% CI; 1.25-10.27)] and previously married [AOR = 5.62; (95% CI: 1.52-20.75)] participants had significantly higher likelihood of HIV infections. Sexually Transmitted Infections [AOR = 2.21; (95% CI: 1.35-3.60)] were more than twice likely associated with HIV infection. One significant (p < 0.05) primary cluster of HIV prevalence around central Uganda emerged from the SaTScan cluster analysis. Spatial analysis disclosed behavioural factors associated with greater odds of HIV infection such as; alcohol use before sexual intercourse [Posterior Odds Ratio (POR) =1.32; 95% (BCI: 1.11-1.63)]. Condom use [POR = 0.54; (95% BCI: 0.41-0.69)] and circumcision [POR = 0.66; (95% BCI: 0.45-0.99)] provided a protective effect against HIV.

Conclusions

The study revealed associations between high-risk sexual behaviour and HIV infection. Behavioural change interventions should therefore be pertinent to the prevention of HIV. Spatial analysis further revealed a significant HIV cluster towards the Central and Eastern areas of Uganda. We propose that interventions targeting young people should initially focus on these regions and subsequently spread out across Uganda.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

BACKGROUND

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level.

METHODS

Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering.

RESULTS

Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts.

CONCLUSIONS

Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Spatial Analysis of Multiple Sclerosis Disease in Tehran Metropolitan Zone, Iran, 2001-2012

BACKGROUND

Multiple Sclerosis (MS) is a disease with high disabling disorders and considerable social and economic impacts. This study was conducted to analyze the spatial distribution of MS disease in Tehran, Iran during 2001-2012.

METHODS

The existing information in the MS patients' medical files who had registered in Iranian MS Society (IMSS), located in Tehran office, was used for analysis. The relationship between diseases incidences in 22 zones of Tehran based on estimated socio-economic status (SES) of each zone was evaluated. High and low clustering approach was used in order to investigate the disease's distribution pattern meanwhile, Getis Ord's Gi test and Hot Spot analysis approach has been used to detect high risk zones of the disease.

RESULTS

A total of 6027 MS patients were registered between 2001- 2012 which 4580 (%75.99) were women. During the study period, zone number 6 figured as the most high risk zone for the disease (P<0.1). A heterogeneous distribution was shown for the disease. Cumulative incidence of the disease in northern zones (101.73 per 100,000 inhabitants) was two times more of Southern zones (53.79 per 100,000 inhabitants). There seems to be a direct linear relationship between estimated incidence rate of the disease in each zones with the level of SES (P<0.001).

CONCLUSION

Heterogeneous geographical distribution of MS and its higher estimated incidence for northern zones in Tehran may be because of higher SES and other factors in mentioned zones. It is recommended to consider the surveillance with long-term and cost-effective interventional strategies along with disease in high risk zones.

Monitoring the impact of decentralised chronic care services on patient travel time in rural Africa--methods and results in Northern Malawi

Background

Decentralised health services form a key part of chronic care strategies in resource-limited settings by reducing the distance between patient and clinic and thereby the time and costs involved in travelling. However, few tools exist to evaluate the impact of decentralisation on patient travel time or what proportion of patients attend their nearest clinic. Here we develop methods to monitor changes in travel time, using data from the antiretroviral therapy (ART) roll-out in a rural district in North Malawi.

Methods

Clinic position was combined with GPS information on the home village of patients accessing ART services in Karonga District (North Malawi) between July 2005 and July 2009. Potential travel time was estimated as the travel time for an individual attending their nearest clinic, and estimated actual travel time as the time to the clinic attended. This allowed us to calculate changes in potential and actual travel time as new clinics opened and track the proportion and origin of patients not accessing their nearest clinic.

Results

The model showed how the opening of further ART clinics in Karonga District reduced median potential travel time from 83 to 43 minutes, and median actual travel time fell from 83 to 47 minutes. The proportion of patients not attending their nearest clinic increased from 6% when two clinics were open, to 12% with four open.

Discussion

Integrating GPS information with patient data shows the impact of decentralisation on travel time and clinic choice to inform policy and research questions. In our case study, travel time decreased, accompanied by an increased uptake of services. However, the model also identified an increasing proportion of ART patients did not attend their nearest clinic.

Body fatness or anthropometry for assessment of unhealthy weight status? Comparison between methods in South African children and adolescents

OBJECTIVE

A variety of methods are available for defining undernutrition (thinness/underweight/under-fat) and overnutrition (overweight/obesity/over-fat). The extent to which these definitions agree is unclear. The present cross-sectional study aimed to assess agreement between widely used methods of assessing nutritional status in children and adolescents, and to examine the benefit of body composition estimates.

DESIGN

The main objective of the cross-sectional study was to assess underweight, overweight and obesity using four methods: (i) BMI-for-age using WHO (2007) reference data; (ii) BMI-for-age using Cole et al. and International Obesity Taskforce cut-offs; (iii) weight-for-age using the National Centre for Health Statistics/WHO growth reference 1977; and (iv) body fat percentage estimated by bio-impedance (body fat reference curves for children of McCarthy et al., 2006). Comparisons were made between methods using weighted kappa analyses.

SETTING

Rural South Africa.

SUBJECTS

Individuals (n 1519) in three age groups (school grade 1, mean age 7 years; grade 5, mean age 11 years; grade 9, mean age 15 years).

RESULTS

In boys, prevalence of unhealthy weight status (both under- and overnutrition) was much higher at all ages with body fatness measures than with simple anthropometric proxies for body fatness; agreement between fatness and weight-based measures was fair or slight using Landis and Koch categories. In girls, prevalence of unhealthy weight status was also higher with body fatness than with proxies, although agreement between measures ranged from fair to substantial.

CONCLUSIONS

Methods for defining under- and overnutrition should not be considered equivalent. Weight-based measures provide highly conservative estimates of unhealthy weight status, possibly more conservative in boys. Simple body composition measures may be more informative than anthropometry for nutritional surveillance of children and adolescents.

Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui

BACKGROUND

The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map.

METHODS

This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes.

RESULTS

Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script.

CONCLUSIONS

This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an educational role for such applications.

Improving maternal and perinatal outcomes in the hypertensive disorders of pregnancy: a vision of a community-focused approach

The hypertensive disorders of pregnancy (HDP; pre-existing hypertension, gestational hypertension, and pre-eclampsia) remain important causes of maternal morbidity and mortality, especially in low- and middle-income countries. The paper summarizes the current state of evidence around possible technologies to support community-based improvements in maternal and perinatal outcomes for women with pre-eclampsia. Through the testing and, where proven, introduction of these technologies, we believe that HDP-related progress toward achieving Millennium Development Goal 5 can best be accelerated. The evidence and discussion are presented under the following headings: (1) prediction; (2) prevention; (3) diagnosis; (4) risk stratification; (5) decision aids; (6) treatment; (7) geographic information systems; (8) communication; and (9) community and patient education.

Filaria monitoring visualization system: a geographical information system-based application to manage lymphatic filariasis in Andhra Pradesh, India

Among various public health diseases, filariasis constitutes a major public health problem in India, wherein an estimated 553.7 million people are at risk of infection. The aim of this article is to present a spatial mapping and analysis of filariasis data over a 3-year period (2004-2007) from Karimnagar, Chittoor, East and West Godavari districts of Andhra Pradesh, India. The data include epidemiological and entomological studies (i.e., infection rate, infectivity rate, mosquito per man hour, and microfilaria rate). These parameters were customized on Geographical Information System (GIS) platform and developed filaria monitoring visualization system (FMVS) for identifying the endemic/risk areas of filariasis among these four districts. GIS map for filariasis transmission from the study areas was created and stratified into different spatial entities like low, medium, and high risk zones. On the basis of the data and FMVS maps, it was demonstrated that filariasis remained unevenly distributed within the districts. Balancing the intervention coverage in different villages with overall mass drug administration and continued promotion of the proper use of control measures are necessary for further reduction of filarial cases in these districts.

Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia

BACKGROUND

Despite the demonstrated utility of GIS for health applications, there are perceived problems in low resource settings: GIS software can be expensive and complex; input data are often of low quality. This study aimed to test the appropriateness of new, inexpensive and simple GIS tools in poorly resourced areas of a developing country. GIS applications were trialled in pilot studies based on mapping of health resources and health indicators at the clinic and district level in the predominantly rural province of Nusa Tenggara Timur in eastern Indonesia. The pilot applications were (i) rapid field collection of health infrastructure data using a GPS enabled PDA, (ii) mapping health indicator data using open source GIS software, and (iii) service availability mapping using a free modelling tool.

RESULTS

Through contextualised training, district and clinic staff acquired skills in spatial analysis and visualisation and, six months after the pilot studies, they were using these skills for advocacy in the planning process, to inform the allocation of some health resources, and to evaluate some public health initiatives.

CONCLUSIONS

We demonstrated that GIS can be a useful and inexpensive tool for the decentralisation of health data analysis to low resource settings through the use of free and simple software, locally relevant training materials and by providing data collection tools to ensure data reliability.

Spatial and socio-behavioral patterns of HIV prevalence in the Democratic Republic of Congo

This study uses a 2007 population-based household survey to examine the individual and community-level factors that increase an individual's risk for HIV infection in the Democratic Republic of Congo (DRC). Using the 2007 DRC Demographic Health Surveillance (DHS) Survey, we use spatial analytical methods to explore sub-regional patterns of HIV infection in the DRC. Geographic coordinates of survey communities are used to map prevalence of HIV infection and explore geographic variables related to HIV risk. Spatial cluster techniques are used to identify hotspots of infection. HIV prevalence is related to individual demographic characteristics and sexual behaviors and community-level factors. We found that the prevalence of HIV within 25 km of an individual's community is an important positive indicator of HIV infection. Distance from a city is negatively associated with HIV infection overall and for women in particular. This study highlights the importance of improved surveillance systems in the DRC and other African countries along with the use of spatial analytical methods to enhance understanding of the determinants of HIV infection and geographic patterns of prevalence, thereby contributing to improved allocation of public health resources in the future.

Spatial analysis of tuberculosis in an urban west African setting: is there evidence of clustering?

OBJECTIVES

To describe the pattern of tuberculosis (TB) occurrence in Greater Banjul, The Gambia with Geographical Information Systems (GIS) and Spatial Scan Statistics (SaTScan) and to determine whether there is significant TB case clustering.

METHODS

In Greater Banjul, where 80% of all Gambian TB cases arise, all patients with TB registered at chest clinics between March 2007 and February 2008 were asked to participate. Demographic, clinical characteristics and GPS co-ordinates for the residence of each consenting TB case were recorded. A spatial scan statistic was used to identify purely spatial and space-time clusters of tuberculosis among permanent residents.

RESULTS

Of 1145 recruited patients with TB, 84% were permanent residents with 88% living in 37 settlements that had complete maps available down to settlement level. Significant high- and low-rate spatial and space-time clusters were identified in two districts. The most likely cluster of high rate from both the purely spatial analysis and the retrospective space-time analysis were from the same geographical area. A significant secondary cluster was also identified in one of the densely populated areas of the study region.

CONCLUSIONS

There is evidence of significant clustering of TB cases in Greater Banjul, The Gambia. Systematic use of cluster detection techniques for regular TB surveillance in The Gambia may aid effective deployment of resources. However, passive case detection dictates that community-based active case detection and risk factor surveys would help confirm the presence of true clusters and their causes.

A trend analysis and sub-regional distribution in number of people living with HIV and dying with TB in Africa, 1991 to 2006

Background

The tuberculosis (TB) bacillus and the Human Immunodeficiency Virus (HIV) have formed a powerful alliance and are together responsible for more than five million deaths per year. TB is leading to increased mortality rates among people living with HIV/acquired immunodeficiency syndrome (AIDS). The aim of this study was to investigate the geographical and temporal distribution of TB-HIV deaths in Africa in order to identify possible high-risk areas.

Methods

Time trends in the 16-year study period from 1990 to 2005 were analyzed by multilevel Poisson growth curve models. Moran global and local indicators of spatial associations were used to test for evidence of global and local spatial clustering respectively.

Results

Eastern, Southern, Western, and Middle Africa experienced an upward trend in the number of reported TB-HIV deaths. The spatial distribution of TB cases was non-random and clustered, with a Moran's I = 0.454 (p = .001). Spatial clustering suggested that 13 countries were at increased risk of TB-HIV deaths, and six countries could be grouped as "hot spots".

Conclusion

Evidence shows that there is no decline in growth in the number of deaths due to TB among HIV positive in most Africa countries. There is presence of 'hot-spots' and very large differences persist between sub-regions. Only by tackling TB and HIV together will progress be made in reversing the burden of both diseases. There is a great need for scale-up of preventive interventions such as the World Health Organization '3I's strategy' (intensified case finding, isoniazid preventive therapy and infection control).

Possible outbreak of streptomycin-resistant Mycobacterium tuberculosis Beijing in Benin

Using geographic information system and molecular tools, we characterized a possible outbreak of tuberculosis caused by Mycobacterium tuberculosis Beijing strain in 17 patients in Cotonou, Benin, during July 2005–October 2006. Most patients lived or worked in the same area and frequented the same local drinking bar. The isolates were streptomycin resistant.

Geographic information system (GIS) maps and malaria control monitoring: intervention coverage and health outcome in distal villages of Khammouane province, Laos

Background

Insecticide-treated nets (ITNs) are a key intervention to control malaria. The intervention coverage varies as a consequence of geographical accessibility to remote villages and limitations of financial and human resources for the intervention. People's adherence to the intervention, i.e., proper use of ITNs, also affects malaria health outcome. The study objective is to explore the impact of the intervention coverage and people's adherence to the intervention on malaria health outcome among targeted villages in various geographic locations.

Methods

Geographic information system (GIS) maps were developed using the data collected in an active case detection survey in Khammouane province, Laos. The survey was conducted using rapid diagnostic tests (RDTs) and a structured questionnaire at 23 sites in the province from June to July, the rainy season, in 2005. A total of 1,711 villagers from 403 households participated in the survey.

Results

As indicated on the GIS maps, villages with malaria cases, lower intervention coverage, and lower adherence were identified. Although no malaria case was detected in most villages with the best access to the district center, several cases were detected in the distal villages, where the intervention coverage and adherence to the intervention remained relatively lower.

Conclusion

Based on the data and maps, it was demonstrated that malaria remained unevenly distributed within districts. Balancing the intervention coverage in the distal villages with the overall coverage and continued promotion of the proper use of ITNs are necessary for a further reduction of malaria cases in the province.