GIS and Health: Enhancing Disease Surveillance and Intervention through Spatial Epidemiology

The success of an evidence-based intervention depends on precise and accurate evaluation of available data and information. Here, the use of robust methods for evidence evaluation is important. Epidemiology, in its conventional form, relies on statistics and mathematics to draw inferences on disease dynamics in affected populations. Interestingly, most of the data used tend to have spatial aspects to them. However, most of these statistical and mathematical methods tend to either neglect these spatial aspects or consider them as artefacts, thereby biasing the resultant estimates. Thankfully, spatial methods allow for evidence evaluation and prediction in epidemiologic data while considering their inherent spatial characteristics. This, thus, promises more precise and accurate estimates.This thesis documents and illustrates the contribution spatial methods and spatial thinking makes to epidemiology through studies carried out in two countries with different heath-data quality realities, Uganda and Sweden. To be able to use spatial methods for epidemiology studies, proper spatial data need to be available, which is not the case in Uganda. Consequently, this study had two main aims: (1) It proposed and implemented a novel way of spatially-enabling patient registry systems in settings where the existing infrastructures do not allow for the collection of patient-level spatial details, prerequisites for fine-scale spatial analyses; (2) Where spatial data were available, spatial methods were used to study associative relationships between health outcomes and exposure factors. Spatial econometrics approaches, especially spatially autoregressive regression models were adopted. Also, consistent with location-specific epidemiologic intervention, the advantages of using spatial scan statistics, Geographically Weighted (Poisson) Regression and local entropy maps to distil model parameter estimates into their inherent spatial heterogeneities were illustrated. Our results illustrated that through the use of mobile and web technologies and leveraging on existing spatial data pools, systems that enable recording and storage of geospatially referenced patient records can be created. Also, spatial methods outperformed conventional statistical approaches, giving refined and more accurate parameter estimates. Finally, our study illustrates that the use of local spatial methods can inform policy and intervention better through the identification of areas with elevated disease burden or those areas worth additional scrutiny as illustrated by our study of HIV-TB coinfection areas in Uganda, the areas with high CVD-air pollution associations in Sweden, and areas with consistently high joint mortality burden for CVD and cancer among the Swedish elderly.Overall, the incorporation of spatial approaches and spatial thinking in epidemiology cannot be overemphasized. First, by enabling the capture of fine-scale personal-level spatial data, our study promises more robust analyses and seamless data integration. Secondly, associative analyses using spatial methods showed improved results. Thirdly, identification of the areas with elevated disease burden makes identifying the primary drivers of the observed local patterns more informed and focused. Ultimately, our results inform healthcare policy and strategic intervention as the most affected areas can easily be zoned out. Therefore, by illustrating these benefits, this study contributes to epidemiology, through spatial methods, especially in the aspects of disease surveillance, informing policy, and driving possible effective intervention

Unlocking the health system barriers to maximise the uptake and utilisation of molecular diagnostics in low- and middle- income country setting

The study was funded by the European and Developing Countries Clinical Trials Partnership (EDCTP), grant TWENDE-EDCTP-CSA-2014-283.Background : Early access to diagnosis is crucial for effective management of any disease including tuberculosis (TB). We investigated the barriers and opportunities to maximise uptake and utilisation of molecular diagnostics in routine healthcare settings. Methods : Using the implementation of World Health Organisation approved TB diagnostics, Xpert MTB/RIF and Line Probe Assay (LPA) as a benchmark we evaluated the barriers and how they could be unlocked to maximise uptake and utilisation of molecular diagnostics. Results : Health officers representing 190 districts/counties participated in the survey across Kenya, Tanzania and Uganda. The survey findings were corroborated by 145 healthcare facility (HCF) audits and 11 policymaker engagement workshops. Xpert MTB/RIF coverage was 66%, falling behind microscopy and clinical diagnosis by 33% and 1% respectively. Stratified by HCF type, Xpert MTB/RIF implementation was 56%, 96% and 95% at district-, regional- and national referral- hospital levels. LPA coverage was 4%, 3% below culture across the three countries. Out of 111 HCFs with Xpert MTB/RIF, 37 (33%) utilised it to full capacity, performing ≥8 tests per day of which 51% of these were level five (zonal consultant and national referral) HCFs. Likewise, 75% of LPA was available at level five HCFs. Underutilisation of Xpert MTB/RIF and LPA was mainly attributed to inadequate- utilities, 26% and human resource, 22%. Underfinancing was the main reason underlying failure to acquire molecular diagnostics. Second to underfinancing was lack of awareness with 33% healthcare administrators and 49% practitioners were unaware of LPA as TB diagnostic. Creation of a health tax and decentralising its management was proposed by policymakers as a booster of domestic financing needed to increase access to diagnostics. Conclusion : Our findings suggest higher uptake and utilisation of molecular diagnostics at tertiary level HCFs contrary to the WHO recommendation. Country-led solutions are crucial for unlocking barriers to increase access to diagnostics.Publisher PDFPeer reviewe

Space–Time Surveillance of COVID-19 Seasonal Clusters : A Case of Sweden

While COVID-19 is a global pandemic, different countries have experienced different morbidity and mortality patterns. We employ retrospective and prospective space–time permutation analysis on COVID-19 positive records across different municipalities in Sweden from March 2020 to February 2021, using data provided by the Swedish Public Health Agency. To the best of our knowledge, this is the first study analyzing nationwide COVID-19 space–time clustering in Sweden, on a season-to-season basis. Our results show that different municipalities within Sweden experienced varying extents of season-dependent COVID-19 clustering in both the spatial and temporal dimensions. The reasons for the observed differences could be related to the differences in the earlier exposures to the virus, the strictness of the social restrictions, testing capabilities and preparedness. By profiling COVID-19 space–time clusters before the introduction of vaccines, this study contributes to public health efforts aimed at containing the virus by providing plausible evidence in evaluating which epidemiologic interventions in the different regions could have worked and what could have not worked

Spatial analysis of HIV-TB co-clustering in Uganda

BACKGROUND: Tuberculosis (TB) is the leading cause of death for individuals infected with Human immunodeficiency virus (HIV). Conversely, HIV is the most important risk factor in the progression of TB from the latent to the active status. In order to manage this double epidemic situation, an integrated approach that includes HIV management in TB patients was proposed by the World Health Organization and was implemented in Uganda (one of the countries endemic with both diseases). To enable targeted intervention using the integrated approach, areas with high disease prevalence rates for TB and HIV need to be identified first. However, there is no such study in Uganda, addressing the joint spatial patterns of these two diseases.METHODS: This study uses global Moran's index, spatial scan statistics and bivariate global and local Moran's indices to investigate the geographical clustering patterns of both diseases, as individuals and as combined. The data used are TB and HIV case data for 2015, 2016 and 2017 obtained from the District Health Information Software 2 system, housed and maintained by the Ministry of Health, Uganda.RESULTS: Results from this analysis show that while TB and HIV diseases are highly correlated (55-76%), they exhibit relatively different spatial clustering patterns across Uganda. The joint TB/HIV prevalence shows consistent hotspot clusters around districts surrounding Lake Victoria as well as northern Uganda. These two clusters could be linked to the presence of high HIV prevalence among the fishing communities of Lake Victoria and the presence of refugees and internally displaced people camps, respectively. The consistent cold spot observed in eastern Uganda and around Kasese could be explained by low HIV prevalence in communities with circumcision tradition.CONCLUSIONS: This study makes a significant contribution to TB/HIV public health bodies around Uganda by identifying areas with high joint disease burden, in the light of TB/HIV co-infection. It, thus, provides a valuable starting point for an informed and targeted intervention, as a positive step towards a TB and HIV-AIDS free community

Fighting Insurgency, Ruining the Environment : the Case of Forest Fires in the Dersim Province of Turkey

Environmental destruction has long been used as a military strategy in times of conflict. A long-term example of environmental destruction in a conflict zone can be found in Dersim/Tunceli province, located in Eastern Turkey. In the last century, at least two military operations negatively impacted Dersim’s population and environment: 1937–38 and 1993–94. Both conflict and environmental destruction in the region continued after the 1990s. Particularly after July 2015, when the brief peace process that began in 2013 ended, conflict between the Turkish state and the Kurdistan Workers’ Party (PKK) resumed and questions arose about the cause of forest fires in Dersim. In this research we investigate whether there is a relationship between conflict and forest fires in Dersim. This is denied by the Turkish state but asserted by many Dersim residents, civil society groups, and political parties. We use a multi-disciplinary approach, combining methods of qualitative analysis of print media (newspapers), social media (Twitter), and local accounts, together with quantitative methods: remote sensing and spatial analysis. Interdisciplinary analysis combining quantitative datasets with in-depth, qualitative data allows a better understanding of the role of conflict in potentially exacerbating the frequency and severity of forest fires. Although we cannot determine the cause of the fires, the results of our statistical analysis suggest a significant relationship between fires and conflict in Dersim, indicating that the incidence of conflicts is generally correlated with the number of fires

Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda

BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.RESULTS: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.CONCLUSION: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning

Analysis of spatial co-occurrence between cancer and cardiovascular disease mortality and its spatial variation among the Swedish elderly (2010–2015)

CVD and cancer are the two leading causes of death worldwide. Improvement in cancer early detection and treatment has resulted in an increased number of cancer survivors. However, many of the survivors tend to develop CVD often leading to their demise. Conversely, people with pre-existing CVD conditions, especially the elderly, have increased chances of developing cancer and dying from the same. The World Health Organization, consequently, recommends joint management of both diseases. However, in Sweden, as with many other countries, few studies have explored the nature of the associations between the two disease mortalities and their spatial variation at a population level. This study uses correlation, global Moran's index and global bivariate Moran's index to investigate national trends of cancer and CVD crude mortality rates in the Swedish elderly. Spatial scan statistics, spatial overlay and local entropy maps were used to analyse for spatial co-occurrence, local joint spatial clustering and associations in the 2010–2015 cancer and CVD crude mortality rates for the Swedish elderly (65+ years). Mortality data were obtained from the Swedish Healthcare Registry. Our results showed that throughout the years of study, the correlation between cancer and CVD crude mortality rates was averagely positive. Spatial correlation analysis (univariate and bivariate) showed that the contribution of the neighbourhood mortality rates to the observed mortality rates was weak, though significant. From cluster analysis, the cancer and CVD crude mortality rates showed differences in clustering spatial scales with CVD clustering at a smaller scale. Finally, local entropy maps showed that cancer and CVD crude mortality rates were not always related across Sweden, but whenever they were, the relationship was mainly positive and linear. This study contributes to cancer and CVD public health efforts in Sweden by identifying areas where the two causes of death spatially co-occur, and where the two exhibit no spatial overlap. This provides a valuable starting ground for more focused studies to identify local drivers and/or informs coordinated targeted intervention in both causes of death

Spatiotemporal Analysis of Nodding Syndrome in Northern Uganda 1990-2014

The emergence of nodding syndrome (NS) in Northern Uganda has generated controversial views with respect to patterns, natural history, and aetiology of the disease which is yet unknown. This study explored spatial patterns of NS using spatial-temporal methods to establish its clustering patterns across both space and time. Village and year of NS onset for individual patients between the years 1990 and 2014 were entered as input for spatial and temporal analysis in the 6 districts in northern Uganda where it is prevalent. Our temporal results showed that NS onset started before the population was moved in Internally Displaced People’s (IDPs) camps. It also shows that NS continued to be reported during the IDPs and after people had left the IDPs. Our spatial and spatiotemporal analysis showed that two periods had persistent NS clusters. These were 2000-2004 and 2010-2014, coinciding with the period when the population was in the IDP camps and when the population was already out of the camps, respectively. Our conclusion is that the view of associating NS outbreak with living conditions in IDP camps is thus coincidental. We, therefore, contend that the actual aetiological factor of NS is still at large

Qualitative assessment of the impact of socioeconomic and cultural barriers on uptake and utilisation of tuberculosis diagnostic and treatment tools in East Africa:a cross-sectional study

Objectives Early diagnosis and timely treatment are key elements of a successful healthcare system. We assessed the role of socioeconomic and cultural norms in accelerating or decelerating uptake and utilisation of health technologies into policy and practice.Setting Secondary and tertiary level healthcare facilities (HCFs) in three East African countries. Level of HCF was selected based on the WHO recommendation for implantation of tuberculosis (TB) molecular diagnostics.Participants Using implementation of TB diagnostics as a model, we purposively selected participants (TB patients, carers, survivors, healthcare practitioners, community members, opinion leaders and policy-makers) based on their role as stakeholders. In-depth interviews, key informant interviews and focus group discussions were held to collect the data between 2016 and 2018. The data were transcribed, translated, coded and analysed by thematic-content analysis.Results A total of 712 individuals participated in the study. Socioeconomic and cultural factors such as poverty, stigma and inadequate knowledge about causes of disease and available remedies, cultural beliefs were associated with low access and utilisation of diagnostic and treatment tools for TB. Poverty made people hesitate to seek formal healthcare resulting in delayed diagnosis and resorting to self-medication and cheap herbal alternatives. Fear of stigma made people hide their sickness and avoid reporting for follow-up treatment visits. Inadequate knowledge and beliefs were fertile ground for aggravated stigma and believing that diseases like TB are caused by spirits and thus cured by spiritual rituals or religious prayers. Cultural norms were also the basis of gender-based imbalance in accessing care, ‘I could not go to hospital without my husband’s permission’, TB survivor.Conclusion Our findings show that socioeconomic and cultural factors are substantial ‘roadblocks’ to accelerating the uptake and utilisation of diagnostic and treatment tools. Resolving these barriers should be given equal attention as is to health system barrier