Mastering geographically weighted regression: key considerations for building a robust model.

Geographically weighted regression (GWR) takes a prominent role in spatial regression analysis, providing a nuanced perspective on the intricate interplay of variables within geographical landscapes (Brunsdon et al., 1998). However, it is essential to have a strong rationale for employing GWR, either as an addition to, or a complementary analysis alongside, non-spatial (global) regression models (Kiani, Mamiya et al., 2023). Moreover, the proper selection of bandwidth, weighting function or kernel types, and variable choices constitute the most critical configurations in GWR analysis (Wheeler, 2021). [...].

Natural variables separate the endemic areas of Clonorchis sinensis and Opisthorchis viverrini along a continuous, straight zone in Southeast Asia.

BACKGROUND: Clonorchiasis and opisthorchiasis, caused by the liver flukes Clonorchis sinensis and Opisthorchis viverrini respectively, represent significant neglected tropical diseases (NTDs) in Asia. The co-existence of these pathogens in overlapping regions complicates effective disease control strategies. This study aimed to clarify the distribution and interaction of these diseases within Southeast Asia. METHODS: We systematically collated occurrence records of human clonorchiasis (n = 1809) and opisthorchiasis (n = 731) across the Southeast Asia countries. Utilizing species distribution models incorporating environmental and climatic data, coupled machine learning algorithms with boosted regression trees, we predicted and distinguished endemic areas for each fluke species. Machine learning techniques, including geospatial analysis, were employed to delineate the boundaries between these flukes. RESULTS: Our analysis revealed that the endemic range of C. sinensis and O. viverrini in Southeast Asia primarily spans across part of China, Vietnam, Thailand, Laos, and Cambodia. During the period from 2000 to 2018, we identified C. sinensis infections in 84 distinct locations, predominantly in southern China (Guangxi Zhuang Autonomous Region) and northern Vietnam. In a stark contrast, O. viverrini was more widely distributed, with infections documented in 721 locations across Thailand, Laos, Cambodia, and Vietnam. Critical environmental determinants were quantitatively analyzed, revealing annual mean temperatures ranging between 14 and 20 °C in clonorchiasis-endemic areas and 24-30 °C in opisthorchiasis regions (P < 0.05). The machine learning model effectively mapped a distinct demarcation zone, demonstrating a clear separation between the endemic areas of these two liver flukes with AUC from 0.9 to1. The study in Vietnam delineates the coexistence and geographical boundaries of C. sinensis and O. viverrini, revealing distinct endemic zones and a transitional area where both liver fluke species overlap. CONCLUSIONS: Our findings highlight the critical role of specific climatic and environmental factors in influencing the geographical distribution of C. sinensis and O. viverrini. This spatial delineation offers valuable insights for integrated surveillance and control strategies, particularly in regions with sympatric transmission. The results underscore the need for tailored interventions, considering regional epidemiological variations. Future collaborations integrating eco-epidemiology, molecular epidemiology, and parasitology are essential to further elucidate the complex interplay of liver fluke distributions in Asia.

Unraveling trends in schistosomiasis: deep learning insights into national control programs in China.

Objectives: To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China. Methods: We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS). Results: The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease. Conclusion: The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.

Influence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year's longitudinal surveillance data: a spatio-temporal modelling study.

BACKGROUND: Urbanization greatly affects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases. Schistosomiasis, a common parasitic disease transmitted by the snail Oncomelania hupensis, is mainly found in areas with population aggregations along rivers and lakes where snails live. Previous studies have suggested that factors related to urbanization may influence the infection risk of schistosomiasis, but this association remains unclear. This study aimed to analyse the effect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China. METHODS: County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected. The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the National Polar-Orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The geographically and temporally weighted regression model (GTWR) was used to quantify the influence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled. The regression coefficient of urbanization was tested for significance (α = 0.05), and the influence of urbanization on schistosomiasis infection risk was analysed over time and across space based on significant regression coefficients. Variables studied included climate, soil, vegetation, hydrology and topography. RESULTS: The mean regression coefficient for urbanization (0.167) is second only to the leached soil area (0.300), which shows that the urbanization is the most important influence factors for schistosomiasis infection risk besides leached soil area. The other important variables are distance to the nearest water source (0.165), mean minimum temperature (0.130), broadleaf forest area (0.105), amount of precipitation (0.073), surface temperature (0.066), soil bulk density (0.037) and grassland area (0.031). The influence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year. During the study period, the significant coefficient of urbanization level increased from - 0.205 to - 0.131. CONCLUSIONS: The influence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous. The urbanization does reduce the risk of schistosomiasis infection to some extend, but the strength of this influence decreases with increasing urbanization. Additionally, the effect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors. This study provides scientific basis for understanding the influence of urbanization on schistosomiasis, and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.

From Snow's map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis.

The history of mapping infectious diseases dates back to the 19th century when Dr John Snow utilised spatial analysis to pinpoint the source of the 1854 cholera outbreak in London, a ground-breaking work that laid the foundation for modern epidemiology and disease mapping (Newsom, 2006). As technology advanced, so did mapping techniques. In the late 20th century, geographic information systems (GIS) revolutionized disease mapping by enabling researchers to overlay diverse datasets to visualise and analyse complex spatial patterns (Bergquist & Manda 2019; Hashtarkhani et al., 2021). The COVID-19 pandemic showed that disease mapping is particularly valuable for optimising prevention and control strategies of infectious diseases by prioritising geographical targeting interventions and containment strategies (Mohammadi et al., 2021). Today, with the aid of highresolution satellite imagery, geo-referenced electronic data collection systems, real-time data feeds, and sophisticated modelling algorithms, disease mapping has become a feasible and accessible tool for public health officials in tracking, managing, and mitigating the spread of infectious diseases at global, regional and local scales (Hay et al., 2013). [...].

The Cytokine Profile in Different Stages of Schistosomiasis Japonica.

To explore and profile the level of cytokines in the sera of patients infected with Schistosoma japonicum to explore the helper T-cell response of patients either at the chronic or advanced stage of the disease. We randomly selected 58 subjects from several areas endemic for schistosomiasis japonica in China and collected serum samples to be tested for 18 different cytokines secreted by (1) Th1/Th2 cells (GM-CSF, IFN-γ, IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-12p70, IL-10, IL-13, IL-18 and TNF-α) and (2) Th9/Th17/Th22/Treg cells (IL-9, IL-17A, IL-21, IL-22, IL-23 and IL-27). The Th1/Th2 cytokines in chronic patients were not significantly different from those in healthy people, while patients with advanced schistosomiasis had higher levels of IL-2, IL-23 and IL-27 and lower levels of IL-18 and IFN-γ. With respect to the Th9/Th17/Th22/Treg cell cytokines, there were higher levels of IL-23. Thus, a limited variation of the cytokine response between the three patient groups was evident, but only in those with advanced infection, while there was no difference between chronic schistosomiasis infection and healthy subjects in this respect. The cytokine expression should be followed in patients with advanced schistosomiasis who show a cytokine pattern of a weakened Th1 cell response and an increased Th17 response.

High-throughput autoantibody profiling of different stages of Schistosomiasis japonica.

Infection by the Schistosoma japonicum can result in acute, chronic and late-stage manifestations. The latter often presents with severe organ failures and premature death. Importantly, infection can also produce autoimmune phenomena reflected by the development of autoantibodies. We wished to explore and profile the presence of autoantibodies in sera of patients with different stages of S. japonicum infection with the added aim of providing a reference assisting diagnosis. Blood samples from 55 patients with chronic and 20 patients with late-stage schistosomiasis japonica together, with a control group of 50 healthy people were randomly investigated against a microarray of 121 different autoantigens. In addition, the frequency of antibodies against Schistosoma egg antigen (SEA) was examined. In the sera from patients with chronic schistosomiasis japonica, 14 different highly expressed autoantibodies were detected, while patients with late-stage schistosomiasis were found to express as many as 43 autoantibody specificities together with a significantly higher frequency of antibodies against SEA compared to the control group. The findings presented suggest that autoantibody-based classification of schistosomiasis japonica represents a promising approach for the elucidation of subtypes of the disease. This approach may reflect differential disease mechanisms, which could ultimately lead to better treatment.

Optimizing allocation of colorectal cancer screening hospitals in Shanghai: a geospatial analysis.

Screening programmes are important for early diagnosis and treatment of colorectal cancer (CRC) but they are not equally efficient in all locations. Depending on which hospital people belong to, they often are not willing to follow up even after a positive result, resulting in a lower-than-expected overall detection rate. Improved allocation of health resources would increase the program's efficiency and assist hospital accessibility. A target population exceeding 70,000 people and 18 local hospitals were included in the investigation of an optimization plan based on a locationallocation model. We calculated the hospital service areas and the accessibility for people in communities to CRC-screening hospitals using the Huff Model and the Two-Step Floating Catchment Area (2SFCA) approach. We found that only 28.2% of the residents with initially a positive screening result had chosen followup with colonoscopy and significant geographical differences in spatial accessibility to healthcare services indeed exist. The lowest accessibility was found in the Southeast, including the Zhangjiang, Jichang and Laogang communities with the best accessibility mainly distributed near the city centre of Lujiazui; the latter also had relatively a high level of what is called "ineffective screening" as it represents wasteful resource allocation. It is recommended that Hudong Hospital should be chosen instead of Punan Hospital as the optimization, which can improve the service population of each hospital and the populations served per colonoscope. Based on our results, changes in hospital configuration in colorectal cancer screening programme are needed to achieve adequate population coverage and equitable facility accessibility. Planning of medical services should be based on the spatial distribution trends of the population served.

Prehistoric human migrations: a prospective subject for modelling using geographical information systems.

Researchers in many fields have discovered the advantage of using geographical information systems (GIS), spatial statistics and computer modelling, but these techniques are only sparingly applied in archaeological research. Writing 30 years ago, Castleford (1992) noted the considerable potential of GIS, but he also felt that its then atemporal structure was a serious flaw. It is clear that the study of dynamic processes suffers if past events cannot be linked to each other, or to the present, but today's powerful tools have overcome this drawback. Importantly, with location and time as key indices, hypotheses about early human population dynamics can be tested and visualized in ways that can potentially reveal hidden relationships and patterns. [...].

High-risk spatiotemporal patterns of cutaneous leishmaniasis: a nationwide study in Iran from 2011 to 2020.

BACKGROUND: Cutaneous leishmaniasis (CL) is a wide-reaching infection of major public health concern. Iran is one of the six most endemic countries in the world. This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020, detecting high-risk zones, while also noting the movement of high-risk clusters. METHODS: On the basis of clinical observations and parasitological tests, data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education. Utilizing spatial scan statistics, we investigated the disease's purely temporal, purely spatial, spatial variation in temporal trends and spatiotemporal patterns. At P = 0.05 level, the null hypothesis was rejected in every instance. RESULTS: In general, the number of new CL cases decreased over the course of the 9-year research period. From 2011 to 2020, a regular seasonal pattern, with peaks in the fall and troughs in the spring, was found. The period of September-February of 2014-2015 was found to hold the highest risk in terms of CL incidence rate in the whole country [relative risk (RR) = 2.24, P < 0.001)]. In terms of location, six significant high-risk CL clusters covering 40.6% of the total area of the country were observed, with the RR ranging from 1.87 to 9.69. In addition, spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency. Finally, five space-time clusters were found. The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period affecting many regions of the country. CONCLUSIONS: Our study has revealed significant regional, temporal, and spatiotemporal patterns of CL distribution in Iran. Over the years, there have been multiple shifts in spatiotemporal clusters, encompassing many different parts of the country from 2011 to 2020. The results reveal the formation of clusters across counties that cover certain parts of provinces, indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries. Such analyses, at a finer geographical scale, such as county level, might provide more precise results than analyses at the scale of the province.

PTEN hamartoma tumour syndrome: case report based on data from the Iranian hereditary colorectal cancer registry and literature review.

BACKGROUND: PTEN hamartoma tumour syndrome (PHTS) is a rare hereditary disorder caused by germline pathogenic mutations in the PTEN gene. This study presents a case of PHTS referred for genetic evaluation due to multiple polyps in the rectosigmoid area, and provides a literature review of PHTS case reports published between March 2010 and March 2022. CASE PRESENTATION: A 39-year-old Iranian female with a family history of gastric cancer in a first-degree relative presented with minimal bright red blood per rectum and resistant dyspepsia. Colonoscopy revealed the presence of over 20 polyps in the rectosigmoid area, while the rest of the colon appeared normal. Further upper endoscopy showed multiple small polyps in the stomach and duodenum, leading to a referral for genetic evaluation of hereditary colorectal polyposis. Whole-exome sequencing led to a PHTS diagnosis, even though the patient displayed no clinical or skin symptoms of the condition. Further screenings identified early-stage breast cancer and benign thyroid nodules through mammography and thyroid ultrasound. METHOD AND RESULTS OF LITERATURE REVIEW: A search of PubMed using the search terms "Hamartoma syndrome, Multiple" [Mesh] AND "case report" OR "case series" yielded 43 case reports, predominantly in women with a median age of 39 years. The literature suggests that patients with PHTS often have a family history of breast, thyroid and endometrial neoplasms along with pathogenic variants in the PTEN/MMAC1 gene. Gastrointestinal polyps are one of the most common signs reported in the literature, and the presence of acral keratosis, trichilemmomas and mucocutaneous papillomas are pathognomonic characteristics of PHTS. CONCLUSION: When a patient presents with more than 20 rectosigmoid polyps, PHTS should be considered. In such cases, it is recommended to conduct further investigations to identify other potential manifestations and the phenotype of PHTS. Women with PHTS should undergo annual mammography and magnetic resonance testing for breast cancer screening from the age of 30, in addition to annual transvaginal ultrasounds and blind suction endometrial biopsies.

Autoantibodies against type I interferons in COVID-19 infection: A systematic review and meta-analysis.

OBJECTIVES: In this study, we aimed to study the rate of autoantibodies against type I interferons (IFNs) in patients with COVID-19 and analyze its dependence on severity of infection and some other variables. METHODS: A systemic review with the search terms: "COVID-19" or "SARS-CoV-2" and "autoantibodies" or "autoantibody" and "IFN" or "interferon" for the period 20 December 2019 to 15 August 2022 was carried out using PubMed, Embase, Cochrane, and Web of Science. R 4.2.1 software was used for meta-analysis of the published results. Pooled risk ratios and 95% confidence intervals (CIs) were calculated. RESULTS: We identified eight studies involving 7729 patients, of whom 5097 (66%) had severe COVID-19 and 2632 (34%) had mild or moderate symptoms. The positive rate of anti-type-I-IFN-autoantibodies in the total dataset was 5% (95% CI, 3-8%), but reached 10% (95% CI, 7-14%) in those with severe infection. The most common subtypes were anti-IFN-α (89%) and anti-IFN-ω (77%). The overall prevalence in male patients was 5% (95% CI, 4-6%), and in female patients 2% (95% CI, 1-3%). CONCLUSION: Severe COVID-19 is associated with high rates of autoantibodies against type-I-IFN and more so in male than female patients.

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis.

There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R2 of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO2, PM10, and O3); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

Mapping schistosomiasis risk in Southeast Asia: a systematic review and geospatial analysis.

BACKGROUND: Schistosomiasis is a water-borne parasitic disease estimated to have infected >140 million people globally in 2019, mostly in sub-Saharan Africa. Within the goal of eliminating schistosomiasis as a public health problem by 2030 in the World Health Organization (WHO) Roadmap for neglected tropical diseases, other regions cannot be neglected. Empirical estimates of the disease burden in Southeast Asia largely remain unavailable. METHODS: We undertook a systematic review to identify empirical survey data on schistosomiasis prevalence in Southeast Asia using the Web of Science, ScienceDirect, PubMed and the Global Atlas of Helminth Infections, from inception to 5 February 2021. We then conducted advanced Bayesian geostatistical analysis to assess the geographical distribution of infection risk at a high spatial resolution (5 × 5 km) using the prevalence, number of infected individuals and doses needed for preventive chemotherapy. RESULTS: We identified 494 Schistosoma japonicum surveys in the Philippines and Indonesia, and 285 in Cambodia and Laos for S. mekongi. The latest estimates suggest that 225 [95% credible interval (CrI): 168-285] thousand in the endemic areas of Southeast Asian population were infected in 2018. The highest prevalence of schistosomiasis was 3.86% (95% CrI: 3.40-4.31) in Laos whereas the lowest was 0.29% in Cambodia (95% CrI: 0.22-0.36). The estimated number of praziquantel doses needed per year was 1.99 million (95% CrI: 1.92-2.03 million) for the entire population in endemic areas of Southeast Asia. CONCLUSIONS: The burden of schistosomiasis remains far from the WHO goal and our estimates highlighted areas to target with strengthened interventions against schistosomiasis.

Does the Geohealth domain require a body of knowledge?

To answer the question if the Geohealth domain requires a body of knowledge (BoK), we need a general understanding of concepts associated with this field. Two years ago, the United Nation (UN) committee of experts on global geospatial information management identified "semantic- and ontology-linked data" as something that "will become essential to support the next generation of autonomous systems" (UN-GGIM, 2020). The term ontology is closely related to BoK. Unlike data models, ontologies are independent of application; they are generic, can be used in different ways and have clear advantages but they are challenging to create and even more difficult to maintain. The brief description below summarizes what ontologies are, why they are needed to support linked data, what the role of the semantic web is, what is already going on within the Geohealth domain on ontologies and how a BoK can assist.

Marcel Tanner, Global Health Specialist "Extraordinaire" Incl Supplementary Materials with Personal Contributions from Renowned Experts.

Marcel Tanner, President of the Swiss Academy of the Sciences, Director emeritus of the Swiss Tropical and Public Health Institute (Swiss TPH), and Professor of Epidemiology and Medical Parasitology at the University of Basel, Switzerland, is indeed extraordinary, especially when considering the broad set of global health issues covered by his research [...].

Swiss-Chinese Cooperation in Tropical Medicine: The Role of Professor Marcel Tanner.

This paper is in honour of Professor Marcel Tanner, President of the Swiss Academies of Arts and Sciences, and former Director of the Swiss Tropical and Public Health Institute (Swiss TPH), in Basel, Switzerland. In the 30 plus years since his first visit to China in 1989, Professor Tanner has tirelessly promoted research collaboration between Switzerland and China on health and tropical diseases through international meetings, scholar exchange, and training of young scientists. As a contribution to Professor Tanner's life's work of collaboration with Chinese scientists, we summarize here ideas conceived, work initiated and major outcomes. His approach, embodied in his flowery expression: "Alps and Himalayas never meet, but Swiss and Chinese can", marked the occasion in 2013 when Xinhua Co., Ltd., a pharmaceutical company in Shandong of China, agreed to produce tribendimidine, a new remedy for tropical helminth infections, that was the fruit of long-term research by scientists at the Swiss TPH in Basel, and National Institute of Parasitic Diseases (NIPD) in Shanghai. This was neither the first nor the last of Professor Tanner's forceful, yet diplomatic influence, and we follow in his footprints when continuing in Swiss-Chinese cooperation in tropical medicine.

COVID-19: Past, present and future.

Not available.

Consideration of COVID-19 beyond the human-centred approach of prevention and control: the ONE-HEALTH perspective.

Most of the new emerging and re-emerging zoonotic virus outbreaks in recent years stem from close interaction with dead or alive infected animals. Since late 2019, the coronavirus disease 2019 (COVID-19) has spread into 221 countries and territories resulting in close to 300 million known infections and 5.4 million deaths in addition to a huge impact on both public health and the world economy. This paper reviews the COVID-19 prevalence in animals, raise concerns about animal welfare and discusses the role of environment in the transmission of COVID-19. Attention is drawn to the One Health concept as it emphasizes the environment in connection with the risk of transmission and establishment of diseases shared between animals and humans. Considering the importance of One Health for an effective response to the dissemination of infections of pandemic character, some unsettled issues with respect to COVID-19 are highlighted.

Homicide rates are spatially associated with built environment and socio-economic factors: a study in the neighbourhoods of Toronto, Canada.

OBJECTIVES: Homicide rate is associated with a large variety of factors and therefore unevenly distributed over time and space. This study aims to explore homicide patterns and their spatial associations with different socioeconomic and built-environment conditions in 140 neighbourhoods of the city of Toronto, Canada. METHODS: A homicide dataset covering the years 2012 to 2021 and neighbourhood-based indicators were analysed using spatial techniques such as Kernel Density Estimation, Global/Local Moran's I and Kulldorff's SatScan spatio-temporal methodology. Geographically weighted regression (GWR) and multi-scale GWR (MGWR) were used to analyse the spatially varying correlations between the homicide rate and independent variables. The latter was particularly suitable for manifested spatial variations between explanatory variables and the homicide rate and it also identified spatial non-stationarities in this connection. RESULTS: The adjusted R2 of the MGWR was 0.53, representing a 4.35 and 3.74% increase from that in the linear regression and GWR models, respectively. Spatial and spatio-temporal high-risk areas were found to be significantly clustered in downtown and the north-western parts of the city. Some variables (e.g., the population density, material deprivation, the density of commercial establishments and the density of large buildings) were significantly associated with the homicide rate in different spatial ways. CONCLUSION: The findings of this study showed that homicide rates were clustered over time and space in certain areas of the city. Socioeconomic and the built environment characteristics of some neighbourhoods were found to be associated with high homicide rates but these factors were different for each neighbourhood.