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Lu Y, Zhu H, Hu Z, He F, Chen G. Epidemic Characteristics, Spatiotemporal Pattern, and Risk Factors of Other Infectious Diarrhea in Fujian Province From 2005 to 2021: Retrospective Analysis. JMIR Public Health Surveill 2023; 9:e45870. [PMID: 38032713 PMCID: PMC10722358 DOI: 10.2196/45870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/03/2023] [Accepted: 09/05/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Other infectious diarrhea (OID) continues to pose a significant public health threat to all age groups in Fujian Province. There is a need for an in-depth analysis to understand the epidemiological pattern of OID and its associated risk factors in the region. OBJECTIVE In this study, we aimed to describe the overall epidemic characteristics and spatiotemporal pattern of OID in Fujian Province from 2005 to 2021 and explore the linkage between sociodemographic and environmental factors and the occurrence of OID within the study area. METHODS Notification data for OID in Fujian were extracted from the China Information System for Disease Control and Prevention. The spatiotemporal pattern of OID was analyzed using Moran index and Kulldorff scan statistics. The seasonality of and short-term impact of meteorological factors on OID were examined using an additive decomposition model and a generalized additive model. Geographical weighted regression and generalized linear mixed model were used to identify potential risk factors. RESULTS A total of 388,636 OID cases were recorded in Fujian Province from January 2005 to December 2021, with an average annual incidence of 60.3 (SD 16.7) per 100,000 population. Children aged <2 years accounted for 50.7% (196,905/388,636) of all cases. There was a steady increase in OID from 2005 to 2017 and a clear seasonal shift in OID cases from autumn to winter and spring between 2005 and 2020. Higher maximum temperature, atmospheric pressure, humidity, and precipitation were linked to a higher number of deseasonalized OID cases. The spatial and temporal aggregations were concentrated in Zhangzhou City and Xiamen City for 17 study years. Furthermore, the clustered areas exhibited a dynamic spreading trend, expanding from the southernmost Fujian to the southeast and then southward over time. Factors such as densely populated areas with a large <1-year-old population, less economically developed areas, and higher pollution levels contributed to OID cases in Fujian Province. CONCLUSIONS This study revealed a distinct distribution of OID incidence across different population groups, seasons, and regions in Fujian Province. Zhangzhou City and Xiamen City were identified as the major hot spots for OID. Therefore, prevention and control efforts should prioritize these specific hot spots and highly susceptible groups.
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Affiliation(s)
- Yixiao Lu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Hansong Zhu
- Fujian Provincial Center for Disease Control and Prevention, The Practice Base on the School of Public Health, Fujian Medical University, Fuzhou, China
| | - Zhijian Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Fei He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Guangmin Chen
- Fujian Provincial Center for Disease Control and Prevention, The Practice Base on the School of Public Health, Fujian Medical University, Fuzhou, China
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Lin H, Zhang R, Wu Z, Li M, Wu J, Shen X, Yang C. Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study. Front Public Health 2023; 11:1155146. [PMID: 37325311 PMCID: PMC10266412 DOI: 10.3389/fpubh.2023.1155146] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 05/11/2023] [Indexed: 06/17/2023] Open
Abstract
Background Internal migrants pose a critical threat to eliminating Tuberculosis (TB) in many high-burden countries. Understanding the influential pattern of the internal migrant population in the incidence of tuberculosis is crucial for controlling and preventing the disease. We used epidemiological and spatial data to analyze the spatial distribution of tuberculosis and identify potential risk factors for spatial heterogeneity. Methods We conducted a population-based, retrospective study and identified all incident bacterially-positive TB cases between January 1st, 2009, and December 31st, 2016, in Shanghai, China. We used Getis-Ord Gi* statistics and spatial relative risk methods to explore spatial heterogeneity and identify regions with spatial clusters of TB cases, and then used logistic regression method to estimate individual-level risk factors for notified migrant TB and spatial clusters. A hierarchical Bayesian spatial model was used to identify the attributable location-specific factors. Results Overall, 27,383 bacterially-positive tuberculosis patients were notified for analysis, with 42.54% (11,649) of them being migrants. The age-adjusted notification rate of TB among migrants was much higher than among residents. Migrants (aOR, 1.85; 95%CI, 1.65-2.08) and active screening (aOR, 3.13; 95%CI, 2.60-3.77) contributed significantly to the formation of TB high-spatial clusters. With the hierarchical Bayesian modeling, the presence of industrial parks (RR, 1.420; 95%CI, 1.023-1.974) and migrants (RR, 1.121; 95%CI, 1.007-1.247) were the risk factors for increased TB disease at the county level. Conclusion We identified a significant spatial heterogeneity of tuberculosis in Shanghai, one of the typical megacities with massive migration. Internal migrants play an essential role in the disease burden and the spatial heterogeneity of TB in urban settings. Optimized disease control and prevention strategies, including targeted interventions based on the current epidemiological heterogeneity, warrant further evaluation to fuel the TB eradication process in urban China.
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Affiliation(s)
- Honghua Lin
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Rui Zhang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Zheyuan Wu
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institutes of Preventive Medicine, Shanghai, China
| | - Minjuan Li
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Jiamei Wu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Xin Shen
- Division of TB and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
- Shanghai Institutes of Preventive Medicine, Shanghai, China
| | - Chongguang Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health, Yale University, New Haven, CT, United States
- Nanshan District Center for Disease Control and Prevention, Shenzhen, Guangdong Province, China
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Adewole DA, Reid S, Oni T, Adebowale AS. Geospatial distribution and bypassing health facilities among National Health Insurance Scheme enrollees: implications for universal health coverage in Nigeria. Int Health 2022; 14:260-270. [PMID: 34185841 PMCID: PMC9070472 DOI: 10.1093/inthealth/ihab039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 03/15/2021] [Accepted: 06/17/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND This study was carried out to enable an assessment of geospatial distribution and access to healthcare facilities under the National Health Insurance Scheme (NHIS) of Nigeria. The findings will be useful for efficient planning and equitable distribution of healthcare resources. METHODS Data, including the distribution of selected health facilities, were collected in Ibadan, Nigeria. The location of all facilities was recorded using Global Positioning System and was subsequently mapped using ArcGIS software to produce spider-web diagrams displaying the spatial distribution of all health facilities. RESULTS The result of clustering analysis of health facilities shows that there is a statistically significant hotspot of health facility at 99% confidence located around the urban areas of Ibadan. The significant hotspot result is dominated by a feature with a high value and is surrounded by other features also with high values. Away from the urban built-up area of Ibadan, health facility clustering is not statistically significant. There was also a high level (94%) of bypassing of NHIS-accredited facilities among the enrollees. CONCLUSIONS Lopsided distribution of health facilities in the study area should be corrected as this may result in inequity of access to available health services.
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Affiliation(s)
- David A Adewole
- Department of Health Policy and Management, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Public Health & Family Medicine, Division of Public Health Medicine, University of Cape Town, Cape Town, South Africa
| | - Steve Reid
- Primary Health Care Directorate, Faculty of Health Sciences, University of Cape Town, E47 OMB Groote Schuur Hospital, Observatory, Cape Town 7925, South Africa
| | - Tolu Oni
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
- Division of Public Health Medicine, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Ayo S Adebowale
- Department of Epidemiology and Medical Statistics, Faculty of Public Health, University of Ibadan, Ibadan, Nigeria
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Mishra PS, Sinha D, Kumar P, Srivastava S. Spatial inequalities in skilled birth attendance in India: a spatial-regional model approach. BMC Public Health 2022; 22:79. [PMID: 35022008 PMCID: PMC8756682 DOI: 10.1186/s12889-021-12436-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 12/17/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Despite a significant increase in the skilled birth assisted (SBA) deliveries in India, there are huge gaps in availing maternity care services across social gradients - particularly across states and regions. Therefore, this study applies the spatial-regression model to examine the spatial distribution of SBA across districts of India. Furthermore, the study tries to understand the spatially associated population characteristics that influence the low coverage of SBA across districts of India and its regions. METHODS The study used national representative cross-sectional survey data obtained from the fourth round of National Family Health Survey, conducted in 2015-16. The effective sample size was 259,469 for the analysis. Moran's I statistics and bivariate Local Indicator for Spatial Association maps were used to understand spatial dependence and clustering of deliveries conducted by SBA coverage in districts of India. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of deliveries conducted by SBA. RESULTS Moran's I value for SBA among women was 0.54, which represents a high spatial auto-correlation of deliveries conducted by SBA over 640 districts of India. There were 145 hotspots for deliveries conducted by SBA among women in India, which includes almost the entire southern part of India. The spatial error model revealed that with a 10% increase in exposure to mass media in a particular district, the deliveries conducted by SBA increased significantly by 2.5%. Interestingly, also with the 10% increase in the four or more antenatal care (ANC) in a particular district, the deliveries conducted by SBA increased significantly by 2.5%. Again, if there was a 10% increase of women with first birth order in a particular district, then the deliveries conducted by SBA significantly increased by 6.1%. If the district experienced an increase of 10% household as female-headed, then the deliveries conducted by SBA significantly increased by 1.4%. CONCLUSION The present study highlights the important role of ANC visits, mass media exposure, education, female household headship that augment the use of an SBA for delivery. Attention should be given in promoting regular ANC visits and strengthening women's education.
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Affiliation(s)
- Prem Shankar Mishra
- Research Scholar, Population Research Centre, Institute for Social and Economic Change, Bengaluru, Karnataka 560072 India
| | - Debashree Sinha
- Research Scholar, Department of Development Studies, International Institute for Population Sciences, Mumbai, Maharashtra 400088 India
| | - Pradeep Kumar
- Research Scholar, Department of Survey Research & Data Analytics, International Institute for Population Sciences, Mumbai, Maharashtra 400088 India
| | - Shobhit Srivastava
- Research Scholar, Department of Survey Research & Data Analytics, International Institute for Population Sciences, Mumbai, Maharashtra 400088 India
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Gwitira I, Karumazondo N, Shekede MD, Sandy C, Siziba N, Chirenda J. Spatial patterns of pulmonary tuberculosis (TB) cases in Zimbabwe from 2015 to 2018. PLoS One 2021; 16:e0249523. [PMID: 33831058 PMCID: PMC8031317 DOI: 10.1371/journal.pone.0249523] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 03/21/2021] [Indexed: 12/19/2022] Open
Abstract
INTRODUCTION Accurate mapping of spatial heterogeneity in tuberculosis (TB) cases is critical for achieving high impact control as well as guide resource allocation in most developing countries. The main aim of this study was to explore the spatial patterns of TB occurrence at district level in Zimbabwe from 2015 to 2018 using GIS and spatial statistics as a preamble to identifying areas with elevated risk for prioritisation of control and intervention measures. METHODS In this study Getis-Ord Gi* statistics together with SaTscan were used to characterise TB hotspots and clusters in Zimbabwe at district level from 2015 to 2018. GIS software was used to map and visualise the results of cluster analysis. RESULTS Results show that TB occurrence exhibits spatial heterogeneity across the country. The TB hotspots were detected in the central, western and southern part of the country. These areas are characterised by artisanal mining activities as well as high poverty levels. CONCLUSIONS AND RECOMMENDATIONS Results of this study are useful to guide TB control programs and design effective strategies which are important in achieving the United Nations Sustainable Development goals (UNSDGs).
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Affiliation(s)
- Isaiah Gwitira
- Department of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, Harare, Zimbabwe
| | - Norbert Karumazondo
- Department of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, Harare, Zimbabwe
| | - Munyaradzi Davis Shekede
- Department of Geography Geospatial Sciences and Earth Observation, Faculty of Science, University of Zimbabwe, Harare, Zimbabwe
| | - Charles Sandy
- National TB Control Program, Ministry of Health and Child Care, Harare, Zimbabwe
| | - Nicolas Siziba
- National TB Control Program, Ministry of Health and Child Care, Harare, Zimbabwe
| | - Joconiah Chirenda
- Department of Community Medicine, Faculty of Medicine and Health Sciences, Parirenyatwa Hospital, University of Zimbabwe, Harare, Zimbabwe
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Gwitira I, Mukonoweshuro M, Mapako G, Shekede MD, Chirenda J, Mberikunashe J. Spatial and spatio-temporal analysis of malaria cases in Zimbabwe. Infect Dis Poverty 2020; 9:146. [PMID: 33092651 PMCID: PMC7584089 DOI: 10.1186/s40249-020-00764-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 10/14/2020] [Indexed: 01/26/2023] Open
Abstract
Background Although effective treatment for malaria is now available, approximately half of the global population remain at risk of the disease particularly in developing countries. To design effective malaria control strategies there is need to understand the pattern of malaria heterogeneity in an area. Therefore, the main objective of this study was to explore the spatial and spatio-temporal pattern of malaria cases in Zimbabwe based on malaria data aggregated at district level from 2011 to 2016. Methods Geographical information system (GIS) and spatial scan statistic were applied on passive malaria data collected from health facilities and aggregated at district level to detect existence of spatial clusters. The global Moran’s I test was used to infer the presence of spatial autocorrelation while the purely spatial retrospective analyses were performed to detect the spatial clusters of malaria cases with high rates based on the discrete Poisson model. Furthermore, space-time clusters with high rates were detected through the retrospective space-time analysis based on the discrete Poisson model. Results Results showed that there is significant positive spatial autocorrelation in malaria cases in the study area. In addition, malaria exhibits spatial heterogeneity as evidenced by the existence of statistically significant (P < 0.05) spatial and space-time clusters of malaria in specific geographic regions. The detected primary clusters persisted in the eastern region of the study area over the six year study period while the temporal pattern of malaria reflected the seasonality of the disease where clusters were detected within particular months of the year. Conclusions Geographic regions characterised by clusters of high rates were identified as malaria high risk areas. The results of this study could be useful in prioritizing resource allocation in high-risk areas for malaria control and elimination particularly in resource limited settings such as Zimbabwe. The results of this study are also useful to guide further investigation into the possible determinants of persistence of high clusters of malaria cases in particular geographic regions which is useful in reducing malaria burden in such areas.
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Affiliation(s)
- Isaiah Gwitira
- Department of Geography Geospatial Sciences and Earth Observation, University of Zimbabwe, P. O. Box MP 167, Mount Pleasant, Harare, Zimbabwe.
| | - Munashe Mukonoweshuro
- Department of Geography Geospatial Sciences and Earth Observation, University of Zimbabwe, P. O. Box MP 167, Mount Pleasant, Harare, Zimbabwe
| | - Grace Mapako
- Department of Geography Geospatial Sciences and Earth Observation, University of Zimbabwe, P. O. Box MP 167, Mount Pleasant, Harare, Zimbabwe
| | - Munyaradzi D Shekede
- Department of Geography Geospatial Sciences and Earth Observation, University of Zimbabwe, P. O. Box MP 167, Mount Pleasant, Harare, Zimbabwe
| | - Joconiah Chirenda
- Department of Community Medicine, University of Zimbabwe, 3rd Floor New Health Sciences Building, College of Health Sciences, P O Box A178, Avondale, Harare, Zimbabwe
| | - Joseph Mberikunashe
- National Malaria Control Program, Ministry of Health and Child Care, 4th Floor, Kaguvi Building, Central Avenue (Between 4th and 5th Street), Harare, Zimbabwe
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