Subjects -> HEALTH AND SAFETY (Total: 1540 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (86 journals)
    - HEALTH AND SAFETY (721 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (390 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (108 journals)
    - PHYSICAL FITNESS AND HYGIENE (131 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH AND SAFETY (721 journals)                  1 2 3 4 | Last

Showing 1 - 200 of 203 Journals sorted alphabetically
16 de Abril     Open Access   (Followers: 4)
Acta Informatica Medica     Open Access   (Followers: 2)
Acta Scientiarum. Health Sciences     Open Access   (Followers: 3)
Adultspan Journal     Hybrid Journal   (Followers: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 12)
Advances in Public Health     Open Access   (Followers: 28)
Adversity and Resilience Science : Journal of Research and Practice     Hybrid Journal   (Followers: 3)
African Health Sciences     Open Access   (Followers: 5)
African Journal for Physical, Health Education, Recreation and Dance     Full-text available via subscription   (Followers: 7)
African Journal of Health Professions Education     Open Access   (Followers: 6)
Afrimedic Journal     Open Access   (Followers: 3)
Ageing & Society     Hybrid Journal   (Followers: 47)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 7)
AJOB Empirical Bioethics     Hybrid Journal   (Followers: 3)
Akademika     Open Access   (Followers: 1)
American Journal of Family Therapy     Hybrid Journal   (Followers: 10)
American Journal of Health Economics     Full-text available via subscription   (Followers: 21)
American Journal of Health Education     Hybrid Journal   (Followers: 36)
American Journal of Health Promotion     Hybrid Journal   (Followers: 34)
American Journal of Health Sciences     Open Access   (Followers: 12)
American Journal of Health Studies     Full-text available via subscription   (Followers: 16)
American Journal of Preventive Medicine     Hybrid Journal   (Followers: 32)
American Journal of Public Health     Full-text available via subscription   (Followers: 279)
American Journal of Public Health Research     Open Access   (Followers: 28)
American Medical Writers Association Journal     Full-text available via subscription   (Followers: 6)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 8)
Annales des Sciences de la Santé     Open Access  
Annali dell'Istituto Superiore di Sanità     Open Access  
Annals of Global Health     Open Access   (Followers: 14)
Annals of Health Law     Open Access   (Followers: 6)
Annals of Tropical Medicine and Public Health     Open Access   (Followers: 15)
Applied Biosafety     Hybrid Journal   (Followers: 1)
Applied Research In Health And Social Sciences: Interface And Interaction     Open Access   (Followers: 5)
Apuntes Universitarios     Open Access   (Followers: 1)
Archive of Community Health     Open Access   (Followers: 1)
Archives of Community Medicine and Public Health     Open Access   (Followers: 2)
Archives of Medicine and Health Sciences     Open Access   (Followers: 5)
Archives of Suicide Research     Hybrid Journal   (Followers: 10)
Archivos de Prevención de Riesgos Laborales     Open Access   (Followers: 1)
Arquivos de Ciências da Saúde     Open Access  
Asia Pacific Journal of Counselling and Psychotherapy     Hybrid Journal   (Followers: 11)
Asia Pacific Journal of Health Management     Full-text available via subscription   (Followers: 5)
Asia-Pacific Journal of Public Health     Hybrid Journal   (Followers: 12)
Asian Journal of Gambling Issues and Public Health     Open Access   (Followers: 4)
Asian Journal of Medicine and Health     Open Access   (Followers: 1)
Atención Primaria     Open Access   (Followers: 2)
Atención Primaria Práctica     Open Access   (Followers: 1)
Australasian Journal of Paramedicine     Open Access   (Followers: 6)
Australian Advanced Aesthetics     Full-text available via subscription   (Followers: 4)
Australian Family Physician     Full-text available via subscription   (Followers: 3)
Australian Indigenous HealthBulletin     Free   (Followers: 5)
Autism & Developmental Language Impairments     Open Access   (Followers: 16)
Behavioral Healthcare     Full-text available via subscription   (Followers: 8)
Bijzijn     Hybrid Journal   (Followers: 1)
Bijzijn XL     Hybrid Journal  
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 8)
Biosafety and Health     Open Access   (Followers: 5)
Biosalud     Open Access   (Followers: 1)
Birat Journal of Health Sciences     Open Access  
BLDE University Journal of Health Sciences     Open Access  
BMC Oral Health     Open Access   (Followers: 7)
BMC Pregnancy and Childbirth     Open Access   (Followers: 24)
BMJ Simulation & Technology Enhanced Learning     Hybrid Journal   (Followers: 12)
Boletin Médico de Postgrado     Open Access  
Brazilian Journal of Medicine and Human Health     Open Access  
British Journal of Health Psychology     Hybrid Journal   (Followers: 50)
Buletin Penelitian Kesehatan     Open Access   (Followers: 2)
Buletin Penelitian Sistem Kesehatan     Open Access  
Bulletin of the World Health Organization     Open Access   (Followers: 23)
Cadernos de Educação, Saúde e Fisioterapia     Open Access   (Followers: 1)
Cadernos de Saúde     Open Access   (Followers: 1)
Cadernos Saúde Coletiva     Open Access   (Followers: 1)
Cambridge Quarterly of Healthcare Ethics     Hybrid Journal   (Followers: 14)
Canadian Family Physician     Partially Free   (Followers: 13)
Canadian Journal of Community Mental Health     Full-text available via subscription   (Followers: 14)
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 3)
Canadian Journal of Public Health     Hybrid Journal   (Followers: 27)
Cannabis and Cannabinoid Research     Hybrid Journal   (Followers: 2)
Carta Comunitaria     Open Access  
Case Reports in Women's Health     Open Access   (Followers: 4)
Case Studies in Fire Safety     Open Access   (Followers: 25)
CASUS : Revista de Investigación y Casos en Salud     Open Access   (Followers: 1)
Central Asian Journal of Global Health     Open Access   (Followers: 2)
CES Medicina     Open Access  
CES Salud Pública     Open Access   (Followers: 1)
Child Abuse Research in South Africa     Full-text available via subscription   (Followers: 1)
Child's Nervous System     Hybrid Journal  
Childhood Obesity and Nutrition     Open Access   (Followers: 11)
Children     Open Access   (Followers: 2)
CHRISMED Journal of Health and Research     Open Access   (Followers: 2)
Christian Journal for Global Health     Open Access  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
Ciencia & Salud     Open Access   (Followers: 2)
Ciencia & Trabajo     Open Access   (Followers: 1)
Ciencia e Innovación en Salud     Open Access  
Ciencia y Cuidado     Open Access   (Followers: 1)
Ciencia y Salud     Open Access   (Followers: 4)
Ciencia y Salud Virtual     Open Access  
Ciencia, Tecnología y Salud     Open Access   (Followers: 2)
Cities & Health     Hybrid Journal   (Followers: 2)
Clinical and Experimental Health Sciences     Open Access   (Followers: 1)
ClinicoEconomics and Outcomes Research     Open Access   (Followers: 2)
Clocks & Sleep     Open Access   (Followers: 2)
CME     Hybrid Journal   (Followers: 2)
CoDAS     Open Access  
Community Health     Open Access   (Followers: 6)
Conflict and Health     Open Access   (Followers: 8)
Contraception and Reproductive Medicine     Open Access   (Followers: 2)
Cuaderno de investigaciones: semilleros andina     Open Access   (Followers: 3)
Cuadernos de la Escuela de Salud Pública     Open Access  
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 10)
Current Opinion in Environmental Science & Health     Hybrid Journal   (Followers: 1)
Das österreichische Gesundheitswesen ÖKZ     Hybrid Journal   (Followers: 1)
Day Surgery Australia     Full-text available via subscription   (Followers: 2)
Design for Health     Hybrid Journal  
Digital Health     Open Access   (Followers: 9)
Disaster Medicine and Public Health Preparedness     Hybrid Journal   (Followers: 14)
Diversity and Equality in Health and Care     Open Access   (Followers: 9)
Diversity of Research in Health Journal     Open Access  
Dramatherapy     Hybrid Journal   (Followers: 3)
Drogues, santé et société     Open Access   (Followers: 2)
Duazary     Open Access   (Followers: 1)
Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi / Journal of Duzce University Health Sciences Institute     Open Access  
Early Childhood Research Quarterly     Hybrid Journal   (Followers: 26)
East African Journal of Public Health     Full-text available via subscription   (Followers: 4)
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity     Hybrid Journal   (Followers: 24)
EcoHealth     Hybrid Journal   (Followers: 5)
Education for Health     Open Access   (Followers: 9)
ElectronicHealthcare     Full-text available via subscription   (Followers: 3)
Elsevier Ergonomics Book Series     Full-text available via subscription   (Followers: 5)
Emergency Services SA     Full-text available via subscription   (Followers: 2)
Ensaios e Ciência : Ciências Biológicas, Agrárias e da Saúde     Open Access  
Environmental Disease     Open Access   (Followers: 4)
Environmental Sciences Europe     Open Access   (Followers: 2)
Epidemics     Open Access   (Followers: 5)
Epidemiologic Perspectives & Innovations     Open Access   (Followers: 6)
Epidemiology, Biostatistics and Public Health     Open Access   (Followers: 22)
EsSEX : Revista Científica     Open Access   (Followers: 1)
Estudios sociales : Revista de alimentación contemporánea y desarrollo regional     Open Access   (Followers: 1)
Ethics & Human Research     Hybrid Journal   (Followers: 3)
Ethics, Medicine and Public Health     Full-text available via subscription   (Followers: 7)
Ethiopian Journal of Health Development     Open Access   (Followers: 7)
Ethiopian Journal of Health Sciences     Open Access   (Followers: 8)
Ethnicity & Health     Hybrid Journal   (Followers: 14)
Eurasian Journal of Health Technology Assessment     Open Access  
EUREKA : Health Sciences     Open Access   (Followers: 2)
European Journal of Investigation in Health, Psychology and Education     Open Access   (Followers: 5)
European Medical, Health and Pharmaceutical Journal     Open Access   (Followers: 1)
Evaluation & the Health Professions     Hybrid Journal   (Followers: 10)
Evidence-based Medicine & Public Health     Open Access   (Followers: 9)
Evidência - Ciência e Biotecnologia - Interdisciplinar     Open Access  
Expressa Extensão     Open Access  
Face à face     Open Access   (Followers: 1)
Families, Systems, & Health     Full-text available via subscription   (Followers: 9)
Family & Community Health     Hybrid Journal   (Followers: 14)
Family Medicine and Community Health     Open Access   (Followers: 10)
Family Relations     Partially Free   (Followers: 15)
Fatigue : Biomedicine, Health & Behavior     Hybrid Journal   (Followers: 2)
Finnish Journal of eHealth and eWelfare : Finjehew     Open Access  
Food and Public Health     Open Access   (Followers: 19)
Food Quality and Safety     Open Access   (Followers: 1)
Frontiers in Digital Health     Open Access   (Followers: 2)
Frontiers in Public Health     Open Access   (Followers: 9)
Frontiers of Health Services Management     Partially Free   (Followers: 4)
Gaceta Sanitaria     Open Access   (Followers: 3)
Galen Medical Journal     Open Access   (Followers: 1)
Ganesha Journal     Open Access  
Gazi Sağlık Bilimleri Dergisi     Open Access  
Geospatial Health     Open Access   (Followers: 1)
Gestão e Desenvolvimento     Open Access  
Gesundheitsökonomie & Qualitätsmanagement     Hybrid Journal   (Followers: 9)
Giornale Italiano di Health Technology Assessment     Full-text available via subscription  
Global Advances in Health and Medicine     Open Access  
Global Challenges     Open Access  
Global Health : Science and Practice     Open Access   (Followers: 8)
Global Health Annual Review     Open Access   (Followers: 4)
Global Health Journal     Open Access   (Followers: 2)
Global Health Promotion     Hybrid Journal   (Followers: 17)
Global Journal of Health Science     Open Access   (Followers: 10)
Global Journal of Public Health     Open Access   (Followers: 14)
Global Medical & Health Communication     Open Access   (Followers: 2)
Global Mental Health     Open Access   (Followers: 9)
Global Reproductive Health     Open Access   (Followers: 1)
Global Security : Health, Science and Policy     Open Access   (Followers: 1)
Global Transitions     Open Access   (Followers: 1)
Globalization and Health     Open Access   (Followers: 9)
Hacia la Promoción de la Salud     Open Access  
Hastane Öncesi Dergisi     Open Access  
Hastings Center Report     Hybrid Journal   (Followers: 5)
HCU Journal     Open Access  
HEADline     Hybrid Journal  
Health & Place     Hybrid Journal   (Followers: 19)
Health & Justice     Open Access   (Followers: 6)
Health : An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine     Hybrid Journal   (Followers: 15)
Health and Human Rights     Open Access   (Followers: 10)
Health and Research Journal     Open Access   (Followers: 4)
Health and Social Care Chaplaincy     Hybrid Journal   (Followers: 11)
Health and Social Work     Hybrid Journal   (Followers: 71)
Health Behavior and Policy Review     Full-text available via subscription   (Followers: 5)
Health Behavior Research     Open Access   (Followers: 6)

        1 2 3 4 | Last

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Geospatial Health
Journal Prestige (SJR): 0.554
Citation Impact (citeScore): 1
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1827-1987 - ISSN (Online) 1970-7096
Published by PAGEPress Homepage  [68 journals]
  • Spatial and spatiotemporal dynamics of visceral leishmaniasis in an
           endemic North-eastern region of Brazil

    • Authors: Ândria Silveira Almeida; Caíque Jordan Nunes Ribeiro, Camila Caroline Carlini, Rogério Silva Santos, Allan Dantas dos Santos, Débora Santos Tavares, Karina Conceicao Gomes Machado de Araújo, Tatiana Rodrigues de Moura, Priscila Lima dos Santos
      Abstract: Visceral Leishmaniasis (VL) is a neglected disease with increasing incidence in Brazil, particularly in the North-eastern. The aim of this study was to analyze the spatial and spatiotemporal dynamics of VL in an endemic region of North-eastern Brazil, between 2009 and 2017. Using spatial analysis techniques, an ecological and time series study was made regarding VL cases in Sergipe filed as notifiable disease events. With data from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística, IBGE), a digital population and cartographic baseline was established. Segmented linear regression was used to examine the temporal trends. The statistical analysis methods of Global and Local Moran’ I, local Bayesian empirical methodology and spatial-temporal scanning were used to produce thematic maps. High instances were found among adults, males, urban residents, non-Whites and persons with low levels of education. A decrease in the recovery rate and an increase in the proportion of urban cases and lethality was found. A heterogeneous VL distribution with spatiotemporal agglomeration on the seaside of the state was seen in Sergipe. To better manage the disease, new research is encouraged together with development of public health strategies. Further, improving health care networks, especially primary care, is suggested as this approach has a key role in health promotion, prevention and monitoring of the most prevalent diseases.
      PubDate: Mon, 11 Jan 2021 11:29:17 +000
       
  • Visualization of schistosomiasis snail habitats using light unmanned
           aerial vehicles

    • Authors: Andrew J. Chamberlin; Isabel J. Jones, Andrea J. Lund, Nicolas Jouanard, Gilles Riveau, Raphaël Ndione, Susanne H. Sokolow, Chelsea L. Wood, Kevin D. Lafferty, Giulio A. De Leo
      Abstract: Schistosomiasis, or “snail fever”, is a parasitic disease affecting over 200 million people worldwide. People become infected when exposed to water containing particular species of freshwater snails. Habitats for such snails can be mapped using lightweight, inexpensive and field-deployable consumer-grade Unmanned Aerial Vehicles (UAVs), also known as drones. Drones can obtain imagery in remote areas with poor satellite imagery. An unexpected outcome of using drones is public engagement. Whereas sampling snails exposes field technicians to infection risk and might disturb locals who are also using the water site, drones are novel and fun to watch, attracting crowds that can be educated about the infection risk.
      PubDate: Fri, 08 Jan 2021 00:00:00 +000
       
  • Spatio-temporal trends and distribution patterns of typhoid disease in
           Uganda from 2012 to 2017

    • Authors: Kamukama Ismail; Gilbert Maiga, Denis Ssebuggwawo, Peter Nabende, Ali Mansourian
      Abstract: Typhoid disease continues to be a global public health burden. Uganda is one of the African countries characterized by high incidences of typhoid disease. Over 80% of the Ugandan districts are endemic for typhoid, largely attributable to lack of reliable knowledge to support disease surveillance. Spatial-temporal studies exploring major characteristics of the disease within the local population have remained limited in Uganda. The main goal of the study was to reveal spatial-temporal trends and distribution patterns of typhoid disease in Uganda for the period 2012 to 2017. Spatial-temporal statistics revealed monthly and annual trends of the disease at both regional and national levels. Results show that outbreaks occurred during 2015 and 2017 in central and eastern regions, respectively. Spatial scan statistic using the discrete Poisson model revealed spatial clusters of the disease for each of the years from 2012 to 2017, together with populations at risk. Most of the disease clustering was in the central region, followed by western and eastern regions (P <0.01). The northern region was the safest throughout the study period. This knowledge helps surveillance teams to i) plan and enforce preventive measures; ii) effectively prepare for outbreaks; iii) make targeted interventions for resource optimization; and iv) evaluate effectiveness of the intervention methods in the study period. This exploratory research forms a foundation of using Geographical Information Systems (GIS) in other related subsequent research studies to discover hidden spatial patterns that are difficult to discover with conventional methods.
      PubDate: Thu, 07 Jan 2021 16:08:53 +000
       
  • Simulation of the spatial distribution of urban populations based on
           first-aid call data

    • Authors: Yinan Zhou; Qin Zhong Zhu, Li Luo
      Abstract: We examined the feasibility of estimating the spatial distribution of urban populations based on first-aid calls based on one high-density place, the Shanghai urban area and one low-density place, the Nanhai District of Foshan City in Guangdong Province. We aggregated the population and the total number of first-aid calls on digital maps divided by grids based on a Geographic Information System (GIS). Geographically weighted regression was applied to test the correlation between the population distribution simulated by first-aid call data and the actual residency. The impact of different population densities, different grid cell sizes and different types of first-aid calls on simulation correlation were tested. We found that the use of first-aid call data could explain 60-95% of the actual population distribution in Shanghai using a grid with 1000*1000 m cell size, while the Nanhai experience was that first-aid calls could only explain 4-76% of the actual population distribution using a grid with 2000*2000 m cell size. Thus, the higher the population density, the better the simulation effect. For a high-population density area, the overall accuracy of simulation can reach as high as 0.878 at the 1-km2 resolution. However, there are different kinds of first-aid calls and for the best estimation of the population distribution in densely populated areas, we suggest using first-aid calls from people requiring acute medical care rather than all first-aid call data.
      PubDate: Tue, 29 Dec 2020 15:05:59 +000
       
  • Mapping the risk for transmission of urban schistosomiasis in the
           Brazilian Northeast

    • Authors: Emília Carolle Azevedo de Oliveira; Iris Edna Pereira da Silva, Ricardo José Ferreira, Ricardo José de Paula Souza e Guimarães, Elainne Christine de Souza Gomes, Constança Simões Barbosa
      Abstract: This is an analysis of the risk of schistosomiasis transmission in the city of Recife in the Northeast of Brazil based on the number of schistosomiasis cases (Schistosoma mansoni) registered for the period 2007-2017 together with data resulting from active search of breeding sites of the Biomphalaria snail intermediate host. The analyses were performed using Kernel Density Estimation (KDE), SaTScan and Map Algebra methodology using human socio-demographic data and biotic and abiotic data from the snail breeding sites. Investigating 44 breeding sites resulted in a total of 3.800 snails, 31.8% of which were positive for S. mansoni DNA. These data were considered in relation to total of 652 schistosomiasis cases. The KDE showed two high-risk and two medium-risk clusters, while three significant clusters were identified by SaTScan. Combining these data with the Map Algebra methodology showed that all high-risk neighbourhoods had breeding sites with snails positive for S. mansoni. It was concluded that schistosomiasis transmission cannot be controlled without basic sanitation and sewage management in the presence of Biomphalaria snails. The technique of Map Algebra was found to be fundamental for the analysis and demonstration of areas with a high probability of schistosomiasis transmission.
      PubDate: Tue, 29 Dec 2020 14:40:41 +000
       
  • Spatiality in small area estimation: A new structure with a simulation
           study

    • Authors: Yadollah Mehrabi; Amir Kavousi, Ahmad-Reza Baghestani, Mojtaba Soltani-Kermanshahi
      Abstract: In numerous practical applications, data from neighbouring small areas present spatial correlation. More recently, an extension of the Fay–Herriot model through the Simultaneously Auto- Rregressive (SAR) process has been considered. The Conditional Auto-Regressive (CAR) structure is also a popular choice. The reasons of using these structures are theoretical properties, computational advantages and relative ease of interpretation. However, the assumption of the non-singularity of matrix (Im-ρW) is a problem. We introduce here a novel structure of the covariance matrix when approaching spatiality in small area estimation (SAE) comparing that with the commonly used SAR process. As an example, we present synthetic data on grape production with spatial correlation for 274 municipalities in the region of Tuscany as base data simulating data at each area and comparing the results. The SAR process had the smallest Root Average Mean Square Error (RAMSE) for all conditions. The RAMSE also generally decreased with increasing sample size. In addition, the RAMSE valuess did not show a specific behaviour but only spatially correlation coefficient changes led to a stronger decrease of RAMSE values than the SAR model when our new structure was applied. The new approach presented here is more flexible than the SAR process without severe increasing RAMSE values.
      PubDate: Tue, 29 Dec 2020 13:42:40 +000
       
  • Understanding the relationship between land use and land cover and malaria
           in Nepal

    • Authors: Shreejana Bhattarai; Korine N. Kolivras, Kabita Ghimire, Yang Shao
      Abstract: Malaria is a leading cause of mortality and morbidity globally. Land Use and Land Cover (LULC) change have been found to affect the transmission of malaria in other regions, but no study has examined such relationships in Nepal. Therefore, this study has three aims: first, to analyze the spatial and temporal trend of Malaria Incidence Rate (MIR) between 1999 and 2015, second to assess LULC change between 2000 and 2010, and finally to understand the relationship between LULC and malaria in Nepal. The land cover types examined are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas, and rice paddies. The temporal trend of MIR and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, and built-up area increased in Nepal by 0.8%, 8.2%, and 28.4% respectively, while other LULC variables decreased between 2000 and 2010. MIR decreased significantly in 21 districts; however, four districts, namely Pyuthan, Kaski, Rupandehi, and Siraha, had a significantly increasing MIR trend between 1999 and 2015. MIR was positively related to water bodies and rice paddies during 2001, 2002, and 2003 but negatively related to grassland during 2010. However, there was no relationship between LULC and MIR during 2000, 2011, 2012 and 2013. This information will be helpful for public health officials to increase control efforts in those districts and in areas near water bodies and rice paddies to aid in their effort to eliminate malaria from Nepal.
      PubDate: Tue, 29 Dec 2020 13:42:01 +000
       
  • Place and Health Infrastructure in the Gulf Cooperation Council: A
           Systematic Scoping Review of GIS Applications in Health

    • Authors: Dari Alhuwail; Saad AlSharrah, Neil T Coffee, Faisal H Al-Refaei, Mark Daniel
      Abstract: The rising burden of non-communicable diseases is taxing health systems globally. Using data science and information systems is necessary to support public health practices. Geographic Information Systems (GIS) are key to inform and help guide public health policies related to place (i.e. location or where one lives) and how it affects health. Despite the increasing use of GIS for public health globally, its applications to health in the Gulf Cooperation Council (GCC) states remains largely unknown. This systematic scoping review aimed to uncover how GIS has been used in the GCC states to understand “place” and “health”. A comprehensive search of the literature was performed in PubMed, Scopus, Science Citation Index Expanded, ScienceDirect, Embase, IEEE Xplore, and ACM Digital Library during June 2020. All journal articles involving the use of GIS for human health applications in the GCC states published in English in peerreviewed scientific journals were considered. After removing duplicates and applying eligibility criteria, qualitative content analysis was performed for 24 of 630 studies. GIS uses in the GCC states were categorized as health access and planning (n=9), health risk analysis (n=8), disease surveillance (n=6) and community health profiling (n=1). The majority of the uncovered evidence in this study focused on the Kingdom of Saudi Arabia. The results of this study indicate a deficiency of published evidence regarding the use of GIS in support of public health in other GCC states. This stands to compromise planning and strategic decision making in health risk analysis, disease surveillance, community health profiling, health services provision and health interventions.
      PubDate: Tue, 29 Dec 2020 13:41:13 +000
       
  • Spatiotemporal analysis of hand, foot and mouth disease data using
           time-lag geographically-weighted regression

    • Authors: Zhi-Min Hong; Hu-Hu Wang, Yan-Juan Wang, Wen-Rui Wang
      Abstract: Hand, Foot, and Mouth Disease (HFMD) is a common and widespread infectious disease. Previous studies have presented evidence that climate factors, including the monthly averages of temperature, relative humidity, air pressure, wind speed and Cumulative Risk (CR) all have a strong influence on the transmission of HFMD. In this paper, the monthly time-lag geographically- weighted regression model was constructed to investigate the spatiotemporal variations of effect of climate factors on HFMD occurrence in Inner Mongolia Autonomous Region, China. From the spatial and temporal perspectives, the spatial and temporal variations of effect of climate factors on HFMD incidence are described respectively. The results indicate that the effect of climate factors on HFMD incidence shows very different spatial patterns and time trends. The findings may provide not only an indepth understanding of spatiotemporal variation patterns of the effect of climate factors on HFMD occurrence, but also provide helpful evidence for making measures of HFMD prevention and control and implementing appropriate public health interventions at the county level in different seasons.
      PubDate: Tue, 29 Dec 2020 11:03:43 +000
       
  • Epidemiological characteristics and determination of spatio-temporal
           clusters during the 2013 dengue outbreak in Chiang Mai, Thailand

    • Authors: Veerasak Punyapornwithaya; Chalutwan Sansamur, Arisara Charoenpanyanet
      Abstract: Dengue is the worldwide most important mosquito-borne viral disease in humans. A large dengue outbreak occurred in Chiang Mai, Thailand in 2013. The aims of this study were to describe the epidemiology of this outbreak and determine the spatio-temporal pattern in the sub-district with the highest number of dengue cases. Data on patients, including date of illness, were obtained from the Chiang Mai Provincial Public Health Center and analyzed descriptively using R statistical software. The geographic location of patients’ residences was determined from available geographical information databases supplemented with coordinated data collection in the field. A space-time permutation model from SaTScan™ was used to determine disease clusters corresponding to space and time. Results showed that Muang District, the centre of the province, had a higher number of cases than the other 25 districts. The Suthep subdistrict, part of Muang District, had most of the patients: 625 subjects distributed between 213 residences. The space-time analysis identified a primary cluster and 7 secondary clusters in different time periods. The primary cluster had 128 patients in a period of approximately 3 months. The number of patients in the secondary clusters ranged between 7 and 65. Most of the clusters occurred in densely populated areas during June and July (the rainy season). The finding from this study may support health agencies to plan surveillance campaigns for people at specified local areas with a high incidence of the disease.
      PubDate: Tue, 29 Dec 2020 10:03:46 +000
       
  • Spatio-temporal distribution characteristics of cysticercosis from 2000 to
           2014 in Dali, Yunnan province, China.

    • Authors: Huanzhang Li; Xinzhong Zang, Xiaokang Hu, Eniola Michael Abe, Menbao Qian, Jingbo Xue, Yingdan Chen, Changhai Zhou, Yuhua Liu, Shizhu Li
      Abstract: Cysticercosis remains a public health problem in China, with disease prevalence attributed to poor socio-economic and public health conditions. This parasitic food-borne disease was prioritized for effective control following implementation of the national surveys on parasitic diseases carried out in China. We predicted the cysticercosis distribution in Dali, Yunnan Province by assessing spatio-temporal distribution characteristics between 2000 and 2014 to better understand the trend of the disease incidence. A database of cysticercosis cases was provided by the clinical department at the Dali Prefectural Institute of Research and Control of Schistosomiasis. Describing the epidemiological features of cysticercosis and analyzing its spatiotemporal distribution of cases using mapping, scanning and spatial autocorrelation analysis, our findings found a total of 3,347 patients with cysticercosis infection, neurocysticercosis in particular. Cysticercosis prevalence was the highest among young and middle-aged male farmers, and also predominant among the Bai nationality. Three aggregation areas were identified during the period 2000-2014. Hotspot analysis implicated Dali City, Eryuan County and Yangbi County between 2000 and 2007, with areas gradually shifting towards the western and northern parts of the province. The hotspot map indicated that Eryuan County was a constant problem with respect to cysticercosis. The results indicated three cysticercosis clusters in Dali that could be attributed to environmental factors and unhealthy lifestyles. Multi-sectoral control initiatives are, therefore, recommended in these areas to effectively control and prevent cysticercosis among the population.
      PubDate: Tue, 29 Dec 2020 09:58:12 +000
       
  • Spatial distribution and sociodemographic risk factors of malaria in
           Nigerian children less than 5 years old

    • Authors: Chigozie Louisa J. Ugwu; Temesgen Zewotir
      Abstract: Malaria remains a leading cause of morbidity and mortality among children in Nigeria less than 5 years old (under-5). This study utilized nationally representative secondary data extracted from the 2015 Nigeria Malaria Indicator Survey (NMIS) to investigate the spatial variability in malaria distribution in those under- 5 and to explore the influence of socioeconomic and demographic factors on malaria prevalence in this population group. To account for spatial correlation, a Spatially Generalized Linear Mixed Model (SGMM) was employed and predictive risk maps was developed using Kriging. Highly significant spatial variability in under-5 malaria distribution was observed (p<0.0001) with a higher likelihood of malaria prevalence in this group in the North-west and North-east of the country. The number of malaria infections increased with age, children aged between 49-59 months were found to be at a higher risk (Odds Ratio=4.680, 95% CI=3.674 to 5.961 at p<0.0001). After accounting for spatial correlation, we observed a strong significant association between the non-availability or non-use of mosquito bed-nets, low household socioeconomic status, low level of mother’s educational attainment, family size, anaemia prevalence, rural type of residence and under-5 malaria prevalence. Faced with a high rate of under-5 mortality due to malaria in Nigeria, targeted interventions (which requires the identification of the child’s location) may reduce malaria prevalence, and we conclude that socioeconomic impediments need to be confronted to reduce the burden of childhood malaria infection.
      PubDate: Tue, 29 Dec 2020 09:48:53 +000
       
  • Hyperendemicity, heterogeneity and spatial overlap of leprosy and
           cutaneous leishmaniasis in the southern Amazon region of Brazil

    • Authors: Amanda Gabriela de Carvalho; João Gabriel Guimarães Luz, João Victor Leite Dias, Anuj Tiwari, Peter Steinmann, Eliane Ignotti
      Abstract: Neglected tropical diseases characterized by skin lesions are highly endemic in the state of Mato Grosso, Brazil. We analyzed the spatial distribution of leprosy and Cutaneous Leishmaniasis (CL) and identified the degree of overlap in their distribution. All new cases of leprosy and CL reported between 2008 and 2017 through the national reporting system were included in the study. Scan statistics together with univariate Global and Local Moran’s I were employed to identify clusters and spatial autocorrelation for each disease, with the spatial correlation between leprosy and CL measured by bivariate Global and Local Moran’s I. Finally, we evaluated the demographic characteristics of the patients. The number of leprosy (N = 28,204) and CL (N = 24,771) cases in Mato Grosso and the highly smoothed detection coefficients indicated hyperendemicity and spatial distribution heterogeneity. Scan statistics demonstrated overlap of high-risk clusters for leprosy (RR = 2.0; p <0.001) and CL (RR = 4.0; p <0.001) in the North and Northeast mesoregions. Global Moran’s I revealed a spatial autocorrelation for leprosy (0.228; p = 0.001) and CL (0.311; p = 0.001) and a correlation between them (0.164; p = 0.001). Both diseases were found to be concentrated in urban areas among men aged 31-60 years, of brown-skinned ethnicity and with a low educational level. Our findings indicate a need for developing integrated and spatially as well as socio-demographically targeted public health policies.
      PubDate: Tue, 29 Dec 2020 09:32:09 +000
       
  • Spatial accessibility to emergency care in Sichuan province in China

    • Authors: Xuefeng Tang; Yufan Deng, Huazhen Yang, Fan Tian, Youping Li, Jay Pan
      Abstract: Timely access to emergency care can substantially improve overall population’s health outcomes. However, currently existed evidence focusing on access to emergency care in China remains insufficient. A better understanding of emergency care from the perspective of spatial accessibility is therefore essential to assist in future healthcare planning. This study provided a brief introduction to the emergency medical service system of China, and assessed the spatial accessibility of emergency care as well as its associated social-economic characteristics based on Sichuan province. Based on populational and hospital administrative data in 2018, we employed the nearest-neighbor method to measure the spatial accessibility while identifying its associated social-economic factors via conventional Ordinary Least Square (OLS) model. The shortest travel time analysis reported a relatively high level of overall spatial accessibility to emergency care in Sichuan. However, substantial geographical disparity in accessibility could nevertheless be observed throughout the province, with the eastern area presenting much higher accessibility than the western area. Regression results suggested that county-level discrepancies in accessibility could be significantly attributed to the variance in local economic development, urbanization level and administrative area. These findings indicated that long-term efforts need to be made by central government on optimizing the allocation of healthcare resources, as well as on fortifying financial support and providing preferential policies for economically disadvantaged regions.
      PubDate: Tue, 29 Dec 2020 09:21:42 +000
       
  • Using object-based image analysis to map commercial poultry operations
           from high resolution imagery to support animal health outbreaks and events
           

    • Authors: Susan Maroney; MaryJane McCool-Eye, Andrew Fox, Christopher Burdett
      Abstract: Precise locations of commercial poultry operations are important to planning and response for animal health outbreaks and events. These data are not available nationally or uniformly in the United States. This project uses machine learning capabilities to identify and map commercial poultry operations from aerial imagery in seven south-eastern states in the United States. The output protocol uses an Object-Based Image Analysis (OBIA) approach, which identifies objects based on spectral signatures combined with spatial, contextual, and textural information. The protocol is a semi-automated and user-assisted process, meaning that the object identification routines require minimal user inputs or expertise. Using the protocol, we produced locations of likely commercial poultry operations in up to two counties in one workday, about two times faster than manual digitisation. The resulting datasets provide an estimate of the number and geographic distribution of commercial poultry operations to assist outbreak response by augmenting available knowledge in affected areas.
      PubDate: Thu, 10 Dec 2020 15:19:40 +000
       
  • Modelling the domestic poultry population in the United States: A novel
           approach leveraging remote sensing and synthetic data methods

    • Authors: Kelly A. Patyk; Mary J. McCool-Eye, David D. South, Christopher L. Burdett, Susan A. Maroney, Andrew Fox, Grace Kuiper, Sheryl Magzamen
      Abstract: Comprehensive and spatially accurate poultry population demographic data do not currently exist in the United States; however, these data are critically needed to adequately prepare for, and efficiently respond to and manage disease outbreaks. In response to absence of these data, this study developed a national-level poultry population dataset by using a novel combination of remote sensing and probabilistic modelling methodologies. The Farm Location and Agricultural Production Simulator (FLAPS) (Burdett et al., 2015) was used to provide baseline national-scale data depicting the simulated locations and populations of individual poultry operations. Remote sensing methods (identification using aerial imagery) were used to identify actual locations of buildings having the characteristic size and shape of commercial poultry barns. This approach was applied to 594 U.S. counties with > 100,000 birds in 34 states based on the 2012 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS), Census of Agriculture (CoA). The two methods were integrated in a hybrid approach to develop an automated machine learning process to locate commercial poultry operations and predict the number and type of poultry for each operation across the coterminous United States. Validation illustrated that the hybrid model had higher locational accuracy and more realistic distribution and density patterns when compared to purely simulated data. The resulting national poultry population dataset has significant potential for application in animal disease spread modelling, surveillance, emergency planning and response, economics, and other fields, providing a versatile asset for further agricultural research.
      PubDate: Thu, 10 Dec 2020 15:10:34 +000
       
  • First year with Covid-19: Assessment and prospects

    • Authors: Robert Bergquist; Behzad Kiani, Samuel Manda
      Abstract: The vision of health for all by Dr. Halfdan Mahler, Director General of the World Health Organization (WHO) 1973 to 1988, guided public health approaches towards improving life for all those mired in poverty and disease. Research on the Neglected Tropical Diseases (NTDs) of the world’s poor was advancing strongly when the coronavirus disease 2019 (Covid-19) struck. (...)
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
  • Spatial association between the incidence rate of Covid-19 and poverty in
           the São Paulo municipality, Brazil

    • Authors: Marcos César Ferreira
      Abstract: In this article, we investigated the spatial dependence of the incidence rate by Covid-19 in the São Paulo municipality, Brazil, including the association between the spatially smoothed incidence rate (INC_EBS) and the social determinants of poverty, the average Salary (SAL), the percentage of households located in slums (SLUMS) and the percentage of the population above 60 years of age (POP>60Y). We used data on the number notified cases accumulated per district by May 18, 2020. The spatial dependence of the spatially smoothed incidence rate was investigated through the analysis of univariate local spatial autocorrelation using Moran’s I. To evaluate the spatial association between the INC_EBS and the determinants SAL, POP>60Y and SLUMS, we used the local bivariate Moran’s I. The results showed that the spatially smoothed incidence rate for Covid-19 presented significant spatial autocorrelation (I = 0.333; p<0.05), indicating that the cases were concentrated in clusters of neighbouring districts. The INC_EBS showed a negative spatial association with SAL (I = - 0.253, p<0.05) and POP>60Y (I = -0.398, p<0.05). We also found that the INC_EBS showed a positive spatial association with households located in the slums (I = 0.237, p<0.05). Our study concluded that the households where the population most vulnerable to Covid-19 resides were spatially distributed in the districts with lower salaries, higher percentages of slums and lower percentages of the population above 60 years of age.
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
  • Investigating spatiotemporal patterns of the Covid-19 in São Paulo
           State, Brazil

    • Authors: Enner Alcântara; José Mantovani, Luiz Rotta, Edward Park, Thanan Rodrigues, Fernando Campos Carvalho, Carlos Roberto Souza Filho
      Abstract: As of 16 May 2020, the number of confirmed cases and deaths in Brazil due to Covid-19 hit 233,142 and 15,633, respectively, making the country one of the most affected by the pandemic. The State of São Paulo (SSP) hosts the largest number of confirmed cases in Brazil, with over 60,000 cases to date. Here we investigate the spatial distribution and spreading patterns of Covid-19 in the SSP by mapping the spatial autocorrelation and the clustering patterns of the virus in relation to the population density and the number of hospital beds. Clustering analysis indicated that São Paulo City is a significant hotspot for both the confirmed cases and deaths, whereas other cities across the state were less affected. Bivariate Moran’s I showed a low relationship between the number of deaths and population density, whereas the number of hospital beds was less related, implying that the fatality depends substantially on the actual patients’ conditions. Multivariate Local Geary showed a positive relationship between the number of deaths and population density, with two cities near São Paulo City being negatively related; the relationship between the number of deaths and hospital beds availability in the São Paulo Metropolitan Area was basically positive. Social isolation measures throughout the State of São Paulo have been gradually increasing since early March, an action that helped to slow down the emergence of the new confirmed cases, highlighting the importance of the safe-distancing measures in mitigating the local transmission within and between cities in the state.
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
  • Spatial and temporal analysis of the Human Immunodeficiency Virus (HIV) in
           an area of social vulnerability in Northeast Brazil

    • Authors: Géssyca Cavalcante de Melo; Emilia Carolle Azevedo de Oliveira, Iane Brito Leal, Carolina Piedade Morais de Freitas Soares Silva, Roberta Andrade Beltrão, Allan Dantas dos Santos, Renata Karina Reis, Marco Antônio Prado Nunes, Karina Conceição Gomes Machado de Araujo
      Abstract: Human Immunodeficiency Virus (HIV) infection still represents an important public health problem, because it involves clinical, epidemiological, social, economic and political issues. We analyzed the temporal and spatial pattern of the HIV incidence in an area of social inequality in northeast Brazil and its association with socioeconomic indicators. An ecological study was carried out with a focus on all HIV cases reported in Alagoas State, Northeast Brazil from 2007 to 2016 using its 102 municipalities as the units of our analysis. Data from the Brazilian information systems were used. Georeferenced data were analyzed using TerraView 4.2.2 software, QGis 2.18.2 and GeoDa 1.14.0. Time trend analyses were performed by the Joinpoint Regression software and the spatial analyses included the empirical Bayesian model and Moran autocorrelation. Spatial regression was used to determine the influence of space on HIV incidence rate and socioeconomic inequalities. There was an increasing trend of HIV rates, especially in the municipalities of the interior. Significant spatial correlations were observed with the formation of clusters with emphasis on the coast of the state and in tourist regions. Spatial regression explained 46% of the dependent variable. The HIV incidence rate was positively influenced by rate of primary health care units (p=0.00), and negatively by Gini index (p = 0.00) and proportion of heads of household without or low education (p=0.02). We conclude that the relationship found between indicators of better socioeconomic conditions and HIV infection suggests unequal access to the diagnosis of infection. Prevention and control strategies can be established according to each epidemiological reality.
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
  • Modelling and analyzing spatial clusters of leptospirosis based on
           satellite-generated measurements of environmental factors in Thailand
           during 2013-2015

    • Authors: Amornrat Luenam; Nattapong Puttanapong
      Abstract: This study statistically identified the association of remotely sensed environmental factors, such as Land Surface Temperature (LST), Night Time Light (NTL), rainfall, the Normalised Difference Vegetation Index (NDVI) and elevation with the incidence of leptospirosis in Thailand based on the nationwide 7,495 confirmed cases reported during 2013–2015. This work also established prediction models based on empirical findings. Panel regression models with random-effect and fixed-effect specifications were used to investigate the association between the remotely sensed environmental factors and the leptospirosis incidence. The Local Indicators of Spatial Association (LISA) statistics were also applied to detect the spatial patterns of leptospirosis and similar results were found (the R2 values of the random-effect and fixed-effect models were 0.3686 and 0.3684, respectively). The outcome thus indicates that remotely sensed environmental factors possess statistically significant contribution in predicting this disease. The highest association in 3 years was observed in LST (random- effect coefficient = -9.787, p<0.001; fixed-effect coefficient = -10.340, p = 0.005) followed by rainfall (random-effect coefficient = 1.353, p <0.001; fixed-effect coefficient = 1.347, p <0.001) and NTL density (random-effect coefficient = -0.569, p = 0.004; fixed-effect coefficient = -0.564, p = 0.001). All results obtained from the bivariate LISA statistics indicated the localised associations between remotely sensed environmental factors and the incidence of leptospirosis. Particularly, LISA’s results showed that the border provinces in the northeast, the northern and the southern regions displayed clusters of high leptospirosis incidence. All obtained outcomes thus show that remotely sensed environmental factors can be applied to panel regression models for incidence prediction, and these indicators can also identify the spatial concentration of leptospirosis in Thailand.
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
  • Leptospirosis and its spatial and temporal relations with natural
           disasters in six municipalities of Santa Catarina, Brazil, from 2000 to
           2016

    • Authors: Ana Elisa Pereira Silva; Francisco Chiaravalloti Neto, Gleice Margarete de Souza Conceição
      Abstract: Leptospirosis is a serious bacterial infection that occurs worldwide, with fatality rate of up to 40% in the most severe cases. The number of cases peaks during the rainy season and may reach epidemic proportions in the event of flooding. It is possible that people living in areas affected by natural disasters are at greater risk of contracting the disease. The aim of this study was to identify clusters of relatively higher risk for leptospirosis occurrence, both in space and time, in six municipalities of Santa Catarina, Brazil, which had the highest incidence of the disease between 2000 and 2016, and to evaluate if these clusters coincide with the occurrence of natural disasters. The cases were geocoded with the geographic coordinates of patients’ home addresses, and the analysis was performed using SaTScan software. The areas mapped as being at risk for hydrological and mass movements were compared with the locations of detected leptospirosis clusters. The disease was more common in men and in the age group from 15 to 69 years. In the scan statistics performed, only space-time showed significant results. Clusters were detected in all municipalities in 2008, when natural disasters preceded by heavy rainfall occurred. One of the municipalities also had clusters in 2011. In these clusters, most of the cases lived in urban areas and areas at risk for experiencing natural disasters. The interaction between time (time of disaster occurrence) and space (areas at risk of experiencing natural disasters) were the determining factors affecting cluster formation.
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
  • Changes in geographic clustering of post-traumatic stress disorder and
           

    • Authors: Marcelo Leiva-Bianchi; Carlos Mena, Yony Ormazábal, Carlos Serrano, Pedro Rojas
      Abstract: Recent findings indicate that both disruptive Post-Traumatic Stress Disorder (PTSD) and healthy Post-Traumatic Growth (PTG) responses have some spatial distribution depending on where they are measured and the different degrees of exposure that people may have to a critical event (e.g., earthquake). Less is known about how these responses change as a function of space and time after these events. The objective of this study was to enter deeper into this relationship analysing how PTSD and PTG responses vary in their spatial distribution 6 and 7 years after an earthquake (such as the one that occurred on 27 February, 2010 in Cauquenes City, Chile). Spatial analyses based on Geographic Information Systems (GIS) were performed to detect global and local geographic clustering. Investigating 171 (2016) and 106 (2017) randomly selected adults from Cauquenes, we demonstrated that 7 years after the event only 4 variables were spatially clustered, i.e. personal mental strength, interpersonal relations, new possibilities and appreciation of life), all of them PTG dimensions; This result contrasted with the situation the previous year (2016), when 7 variables were clustered (total PTG, spiritual change, new possibilities, appreciation of life, PTSD symptoms, PTSD reactions and PTSD in total). The spatial identifications found could facilitate the comparison of mental health conditions in populations and the impact of recovery programmes in communities exposed to disasters.
      PubDate: Thu, 26 Nov 2020 00:00:00 +000
       
 
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