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Li W, Wang J, Huang W, Yan Y, Liu Y, Zhao Q, Chen M, Yang L, Guo Y, Ma W. The association between humidex and tuberculosis: a two-stage modelling nationwide study in China. BMC Public Health 2024; 24:1289. [PMID: 38734652 PMCID: PMC11088084 DOI: 10.1186/s12889-024-18772-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 05/03/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND Under a changing climate, the joint effects of temperature and relative humidity on tuberculosis (TB) are poorly understood. To address this research gap, we conducted a time-series study to explore the joint effects of temperature and relative humidity on TB incidence in China, considering potential modifiers. METHODS Weekly data on TB cases and meteorological factors in 22 cities across mainland China between 2011 and 2020 were collected. The proxy indicator for the combined exposure levels of temperature and relative humidity, Humidex, was calculated. First, a quasi-Poisson regression with the distributed lag non-linear model (DLNM) was constructed to examine the city-specific associations between humidex and TB incidence. Second, a multivariate meta-regression model was used to pool the city-specific effect estimates, and to explore the potential effect modifiers. RESULTS A total of 849,676 TB cases occurred in the 22 cities between 2011 and 2020. Overall, a conspicuous J-shaped relationship between humidex and TB incidence was discerned. Specifically, a decrease in humidex was positively correlated with an increased risk of TB incidence, with a maximum relative risk (RR) of 1.40 (95% CI: 1.11-1.76). The elevated RR of TB incidence associated with low humidex (5th humidex) appeared on week 3 and could persist until week 13, with a peak at approximately week 5 (RR: 1.03, 95% CI: 1.01-1.05). The effects of low humidex on TB incidence vary by Natural Growth Rate (NGR) levels. CONCLUSION A J-shaped exposure-response association existed between humidex and TB incidence in China. Humidex may act as a better predictor to forecast TB incidence compared to temperature and relative humidity alone, especially in regions with higher NGRs.
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Affiliation(s)
- Wen Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Jia Wang
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenzhong Huang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yu Yan
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Yanming Liu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Mingting Chen
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Liping Yang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Wei Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
- Shandong University Climate Change and Health Center, Jinan, Shandong, China.
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Ma Z, Fan H. Influential factors of tuberculosis in mainland China based on MGWR model. PLoS One 2023; 18:e0290978. [PMID: 37651412 PMCID: PMC10470953 DOI: 10.1371/journal.pone.0290978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 08/20/2023] [Indexed: 09/02/2023] Open
Abstract
Tuberculosis (TB), as a respiratory infectious disease, has damaged public health globally for decades, and mainland China has always been an area with high incidence of TB. Since the outbreak of COVID-19, it has seriously occupied medical resources and affected medical treatment of TB patients. Therefore, the authenticity and reliability of TB data during this period have also been questioned by many researchers. In response to this situation, this paper excludes the data from 2019 to the present, and collects the data of TB incidence in mainland China and the data of 11 influencing factors from 2014 to 2018. Using spatial autocorrelation methods and multiscale geographically weighted regression (MGWR) model to study the temporal and spatial distribution of TB incidence in mainland China and the influence of selected influencing factors on TB incidence. The experimental results show that the distribution of TB patients in mainland China shows spatial aggregation and spatial heterogeneity during this period. And the R2 and the adjusted R2 of MGWR model are 0.932 and 0.910, which are significantly better than OLS model (0.466, 0.429) and GWR model (0.836, 0.797). The fitting accuracy indicators MAE, MSE and MAPE of MGWR model reached 5.802075, 110.865107 and 0.088215 respectively, which also show that the overall fitting effect is significantly better than OLS model (19.987574, 869.181549, 0.314281) and GWR model (10.508819, 267.176741, 0.169292). Therefore, this model is based on real and reliable TB data, which provides decision-making references for the prevention and control of TB in mainland China and other countries.
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Affiliation(s)
- Zhipeng Ma
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
| | - Hong Fan
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
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Teibo TKA, Andrade RLDP, Rosa RJ, Tavares RBV, Berra TZ, Arcêncio RA. Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review. BMC Public Health 2023; 23:1586. [PMID: 37598144 PMCID: PMC10439548 DOI: 10.1186/s12889-023-16493-y] [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: 06/08/2023] [Accepted: 08/09/2023] [Indexed: 08/21/2023] Open
Abstract
INTRODUCTION The objective of this systematic review is to identify tuberculosis (TB) high-risk among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis. METHODS The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar. RESULTS A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot's location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%). CONCLUSION There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB.
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Affiliation(s)
- Titilade Kehinde Ayandeyi Teibo
- Department of Maternal-Infant and Public Health Nursing, Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Sao Paulo, Brazil.
| | - Rubia Laine de Paula Andrade
- Department of Maternal-Infant and Public Health Nursing, Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Sao Paulo, Brazil
| | - Rander Junior Rosa
- Department of Maternal-Infant and Public Health Nursing, Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Sao Paulo, Brazil
| | - Reginaldo Bazon Vaz Tavares
- Department of Maternal-Infant and Public Health Nursing, Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Sao Paulo, Brazil
| | - Thais Zamboni Berra
- Department of Maternal-Infant and Public Health Nursing, Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Sao Paulo, Brazil
| | - Ricardo Alexandre Arcêncio
- Department of Maternal-Infant and Public Health Nursing, Ribeirão Preto College of Nursing, University of São Paulo, Ribeirão Preto, Sao Paulo, Brazil
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Wu Z, Fu G, Wen Q, Wang Z, Shi LE, Qiu B, Wang J. Spatiotemporally Comparative Analysis of HIV, Pulmonary Tuberculosis, HIV-Pulmonary Tuberculosis Coinfection in Jiangsu Province, China. Infect Drug Resist 2023; 16:4039-4052. [PMID: 37383602 PMCID: PMC10296641 DOI: 10.2147/idr.s412870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/15/2023] [Indexed: 06/30/2023] Open
Abstract
Purpose Pulmonary tuberculosis (PTB) is a severe chronic communicable disease that causes a heavy disease burden in China. Human Immunodeficiency Virus (HIV) and PTB coinfection dramatically increases the risk of death. This study analyzes the spatiotemporal dynamics of HIV, PTB and HIV-PTB coinfection in Jiangsu Province, China, and explores the impact of socioeconomic determinants. Patients and Methods The data on all notified HIV, PTB and HIV-PTB coinfection cases were extracted from Jiangsu Provincial Center for Disease Control and Prevention. We applied the seasonal index to identify high-risk periods of the disease. Time trend, spatial autocorrelation and SaTScan were used to analyze temporal trends, hotspots and spatiotemporal clusters of diseases. The Bayesian space-time model was conducted to examine the socioeconomic determinants. Results The case notification rate (CNR) of PTB decreased from 2011 to 2019 in Jiangsu Province, but the CNR of HIV and HIV-PTB coinfection had an upward trend. The seasonal index of PTB was the highest in March, and its hotspots were mainly distributed in the central and northern parts, such as Xuzhou, Suqian, Lianyungang and Taizhou. HIV had the highest seasonal index in July and HIV-PTB coinfection had the highest seasonal index in June, with their hotspots mainly distributed in southern Jiangsu, involving Nanjing, Suzhou, Wuxi and Changzhou. The Bayesian space-time interaction model showed that socioeconomic factor and population density were negatively correlated with the CNR of PTB, and positively associated with the CNR of HIV and HIV-PTB coinfection. Conclusion The spatial heterogeneity and spatiotemporal clusters of PTB, HIV and HIV-PTB coinfection are exhibited obviously in Jiangsu. More comprehensive interventions should be applied to target TB in the northern part. While in southern Jiangsu, where the economic level is well-developed and the population density is high, we should strengthen the prevention and control of HIV and HIV-PTB coinfection.
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Affiliation(s)
- Zhuchao Wu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
| | - Gengfeng Fu
- Department of STI and HIV Control and Prevention, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, People’s Republic of China
| | - Qin Wen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
| | - Zheyue Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
| | - Lin-en Shi
- Department of STI and HIV Control and Prevention, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, People’s Republic of China
| | - Beibei Qiu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
| | - Jianming Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
- Department of Epidemiology, Gusu School, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
- Changzhou Medical Center, Nanjing Medical University, Nanjing, 211166, People’s Republic of China
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Lee SM, Jung JH, Lee J, Choi EY, Shin JY, Kim M. Clinical Features, Long-Term Outcomes, and Prognostic Factors of Eales' Disease in Korean Patients. Ocul Immunol Inflamm 2023:1-7. [PMID: 36897992 DOI: 10.1080/09273948.2023.2183870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
PURPOSE We studied Korean patients with Eales' disease to document clinical features, long-term outcomes, and explore its association with TB, given South Korea's high TB burden. METHODS We retrospectively reviewed medical records of Eales' disease patients for clinical characteristics, long-term outcomes, and its association with TB. RESULTS Among 106 eyes, the average age of diagnosis was 39.28 years, with 82.7% male and 58.7% having unilateral involvement. Patients who underwent vitrectomy showed greater long-term improvement in visual acuity (P = .047), while those with glaucoma filtration surgery showed less improvement (P = .008). Having glaucoma through disease progression was associated with poor visual outcomes (odds ratio=15.556, P < .02). 27 out of 39 patients (69.23%) who underwent IGRA screening tested positive for TB. CONCLUSIONS In Korean patients with Eales' disease, we observed male predominance, unilateral presentation, older age of onset, and a link with TB. Timely diagnosis and management should be considered to maintain good vision in patients with Eales' disease.
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Affiliation(s)
- Seung Min Lee
- Department of Ophthalmology, Institute of Vision Research, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jae Hoon Jung
- Department of Ophthalmology, Institute of Vision Research, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Junwon Lee
- Department of Ophthalmology, Institute of Vision Research, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eun Young Choi
- Department of Ophthalmology, Institute of Vision Research, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Joo Youn Shin
- Department of Ophthalmology, Yongin Severance Hospital, Yonsei University College of Medicine, Yonginsi, Republic of Korea
| | - Min Kim
- Department of Ophthalmology, Institute of Vision Research, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
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Zhao R, Miao W, Li B. The Relation Between Trace Elements and Latent Tuberculosis Infection: a Study Based on National Health and Nutritional Examination Survey 2011-2012. Biol Trace Elem Res 2023; 201:1080-1089. [PMID: 35482174 DOI: 10.1007/s12011-022-03240-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/05/2022] [Indexed: 02/07/2023]
Abstract
This study aimed to analyze the potential association between trace elements and latent tuberculosis infection (LTBI) based on the data from the National Health and Nutritional Examination Survey (NHANES) during 2011-2012. In this cross-sectional study, tuberculin skin testing (TST) and QuantiFERON®-TB Gold In-Tube (QFT-GIT) were utilized to screen for LTBI. Participants with positive results of TST or/and QFT-GIT were defined as LTBI. Weighted univariate and multivariate logistic regression analyses were used to explore the association between trace elements and LTBI. Subgroup analyses were conducted according to gender, age, birthplace, race, and health insurance holding status. A total of 6064 participants were included in this study, of whom 655 (10.80%) participants were with positive results of LTBI. Weighted multivariable analysis demonstrated that zinc [odds ratio (OR) = 0.89; 95% confidence interval (CI), 0.82-0.97] and selenium (OR = 0.31; 95%CI, 0.13-0.70) in the serum may be associated with a reduced risk of LTBI. In different concentrations of zinc and selenium, serum zinc concentration of 12.56-13.99 μmol/l (vs. < 11.23 μmol/l; OR = 0.37, 95% CI, 0.20-0.67) was related to a reduced risk of LTBI, while no significant difference was observed under different selenium levels (P > 0.05). Subgroup analyses indicated that the role of zinc and selenium in reducing TB risk may be more significant in males, people aged 21-64, people born in the USA, people with health insurance, and non-Hispanic Whites. Maintaining serum zinc and selenium levels may help reduce the risk of LTBI and indirectly help people prevent TB.
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Affiliation(s)
- Rui Zhao
- Department of Respiratory and Critical Care Medicine, Chifeng Municipal Hospital, Chifeng, 024000, People's Republic of China
| | - Wei Miao
- Department of Endocrinology, Chifeng Municipal Hospital, Chifeng, 024000, People's Republic of China
| | - Baohua Li
- Department of Infectious Disease, Dingxi People's Hospital, No. 22 Anding Road, Dingxi, 743000, People's Republic of China.
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Mavragani A, Xia L, Wu J, Zhou Z, Zhang W, Luan R. The Environmental and Socioeconomic Effects and Prediction of Patients With Tuberculosis in Different Age Groups in Southwest China: A Population-Based Study. JMIR Public Health Surveill 2023; 9:e40659. [PMID: 36456535 PMCID: PMC9883735 DOI: 10.2196/40659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/04/2022] [Accepted: 12/01/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND While the End Tuberculosis (TB) Strategy has been implemented worldwide, the cause of the TB epidemic is multifactorial and not fully understood. OBJECTIVE This study aims to investigate the risk factors of TB and incorporate these factors to forecast the incidence of TB infection across different age groups in Sichuan, China. METHODS Correlation and linear regression analyses were conducted to assess the relationships between TB cases and ecological factors, including environmental, economic, and social factors, in Sichuan Province from 2006 to 2017. The transfer function-noise model was used to forecast trends, considering both time and multifactor effects. RESULTS From 2006 to 2017, Sichuan Province had a reported cumulative incidence rate of 1321.08 cases per 100,000 individuals in male patients and 583.04 cases per 100,000 individuals in female patients. There were significant sex differences in the distribution of cases among age groups (trend χ225=12,544.4; P<.001). Ganzi Tibetan Autonomous Prefecture had the highest incidence rates of TB in both male and female patients in Sichuan. Correlation and regression analyses showed that the total illiteracy rate and average pressure at each measuring station (for individuals aged 15-24 years) were risk factors for TB. The protective factors were as follows: the number of families with the minimum living standard guarantee in urban areas, the average wind speed, the number of discharged patients with invasive TB, the number of people with the minimum living standard guarantee in rural areas, the total health expenditure as a percentage of regional gross domestic product, and being a single male individual (for those aged 0-14 years); the number of hospitals and number of health workers in infectious disease hospitals (for individuals aged 25-64 years); and the amount of daily morning and evening exercise, the number of people with the urban minimum living standard guarantee, and being married (for female individuals aged ≥65 years). The transfer function-noise model indicated that the incidence of TB in male patients aged 0-14 and 15-24 years will continue to increase, and the incidence of TB in female patients aged 0-14 and ≥65 years will continue to increase rapidly in Sichuan by 2035. CONCLUSIONS The End TB Strategy in Sichuan should consider environmental, educational, medical, social, personal, and other conditions, and further substantial efforts are needed especially for male patients aged 0-24 years, female patients aged 0-14 years, and female patients older than 64 years.
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Affiliation(s)
| | - Lan Xia
- Department of Tuberculosis, Center for Disease Control and Prevention of Sichuan Province, Chengdu, China
| | - Jianlin Wu
- Department of Tuberculosis, Center for Disease Control and Prevention of Sichuan Province, Chengdu, China
| | - Zonglei Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Rongsheng Luan
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Rodriguez-Villamizar LA, Marín D, Piñeros-Jiménez JG, Rojas-Sánchez OA, Serrano-Lomelin J, Herrera V. Intraurban Geographic and Socioeconomic Inequalities of Mortality in Four Cities in Colombia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:992. [PMID: 36673751 PMCID: PMC9859133 DOI: 10.3390/ijerph20020992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/22/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
Mortality inequalities have been described across Latin American countries, but less is known about inequalities within cities, where most populations live. We aimed to identify geographic and socioeconomic inequalities in mortality within the urban areas of four main cities in Colombia. We analyzed mortality due to non-violent causes of diseases in adults between 2015 and 2019 using census sectors as unit of analysis in Barranquilla, Bogotá, Cali, and Medellín. We calculated smoothed Bayesian mortality rates as main health outcomes and used concentration indexes (CInd) for assessing inequalities using the multidimensional poverty index (MPI) as the socioeconomic measure. Moran eigenvector spatial filters were calculated to capture the spatial patterns of mortality and then used in multivariable models of the association between mortality rates and quintiles of MPI. Social inequalities were evident but not consistent across cities. The most disadvantaged groups showed the highest mortality rates in Cali. Geographic inequalities in mortality rates, regardless of the adults and poverty distribution, were identified in each city, suggesting that other social, environmental, or individual conditions are impacting the spatial distribution of mortality rates within the four cities.
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Affiliation(s)
| | - Diana Marín
- School of Medicine, Universidad Pontificia Bolivariana, Medellin 050031, Colombia
| | | | - Oscar Alberto Rojas-Sánchez
- Division of Public Health Research, Project Bank Team, National Institute of Health-INS Colombia, Bogotá 111321, Colombia
| | | | - Victor Herrera
- Department of Public Health, School of Medicine, Universidad Industrial de Santander, Bucaramanga 681012, Colombia
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Fahdhienie F, Sitepu FY. Spatio-temporal analysis of tuberculosis incidence in North Aceh District, Indonesia 2019-2021. GEOSPATIAL HEALTH 2022; 17. [PMID: 36468588 DOI: 10.4081/gh.2022.1148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 10/30/2022] [Indexed: 06/17/2023]
Abstract
Tuberculosis (TB) infection continues to present as a leading cause of morbidity and mortality in North Aceh District, Aceh Province, Indonesia. Local TB spatial risk factors have been investigated but space-time clusters of TB in the district have not yet been the subject of study. To that end, research was undertaken to detect clusters of TB incidence during 2019-2021 in this district. First, the office of each of the 27 sub-districts wasgeocoded by collecting data of their geographical coordinates. Then, a retrospective space-time scan statistics analysis based on population data and annual TB incidence was performed using SaTScan TM v9.4.4. The Poisson model was used to identify the areas at high risk of TB and the clusters found were ranked by their likelihood ratio (LLR), with the significance level set at 0.05.There were 2,266 TB cases reported in North Aceh District and the annualized average incidence was 122.91 per 100,000 population. The SaTScan analysis identified that there were three most like clusters and ten secondary clusters, while Morans'Ishowed that there was spatial autocorrelation of TB in the district. The sub-district of GeureudongPase was consistently the location of most likely clusters. The indicators showed that there were significant differences between TB data before the COVID-19 pandemic and those found during the study period. These findings may assist health authorities to improve the TB preventive strategies and develop public health interventions, with special reference to the areas where the clusters were found.
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Affiliation(s)
- Farrah Fahdhienie
- Faculty of Public Health, University of Muhammadiyah Aceh, Banda Aceh, Aceh.
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Investigating Spatial Patterns of Pulmonary Tuberculosis and Main Related Factors in Bandar Lampung, Indonesia Using Geographically Weighted Poisson Regression. Trop Med Infect Dis 2022; 7:tropicalmed7090212. [PMID: 36136622 PMCID: PMC9502094 DOI: 10.3390/tropicalmed7090212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/15/2022] [Accepted: 08/22/2022] [Indexed: 11/16/2022] Open
Abstract
Tuberculosis (TB) is a highly infectious disease, representing one of the major causes of death worldwide. Sustainable Development Goal 3.3 implies a serious decrease in the incidence of TB cases. Hence, this study applied a spatial analysis approach to investigate patterns of pulmonary TB cases and its drivers in Bandar Lampung (Indonesia). Our study examined seven variables: the growth rate of pulmonary TB, population, distance to the city center, industrial area, green open space, built area, and slum area using geographically weighted Poisson regression (GWPR). The GWPR model demonstrated excellent results with an R2 and adjusted R2 of 0.96 and 0.94, respectively. In this case, the growth rate of pulmonary TB and population were statistically significant variables. Spatial pattern analysis of sub-districts revealed that those of Panjang and Kedaton were driven by high pulmonary TB growth rate and population, whereas that of Sukabumi was driven by the accumulation of high levels of industrial area, built area, and slums. For these reasons, we suggest that local policymakers implement a variety of infectious disease prevention and control strategies based on the spatial variation of pulmonary TB rate and its influencing factors in each sub-district.
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Ren H, Lu W, Li X, Shen H. Specific urban units identified in tuberculosis epidemic using a geographical detector in Guangzhou, China. Infect Dis Poverty 2022; 11:44. [PMID: 35428318 PMCID: PMC9012046 DOI: 10.1186/s40249-022-00967-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 04/07/2022] [Indexed: 12/11/2022] Open
Abstract
Background A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB’s spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale. Methods This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales. Results Owing to its strong spatial autocorrelation (Moran’s I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density. Conclusions The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China’s municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s40249-022-00967-z.
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Im C, Kim Y. Local Characteristics Related to SARS-CoV-2 Transmissions in the Seoul Metropolitan Area, South Korea. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182312595. [PMID: 34886318 PMCID: PMC8656497 DOI: 10.3390/ijerph182312595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/26/2021] [Accepted: 11/27/2021] [Indexed: 12/16/2022]
Abstract
The Seoul metropolitan area is one of the most populated metropolitan areas in the world; hence, Seoul's COVID-19 cases are highly concentrated. This study identified local demographic and socio-economic characteristics that affected SARS-CoV-2 transmission to provide locally targeted intervention policies. For the effective control of outbreaks, locally targeted intervention policies are required since the SARS-CoV-2 transmission process is heterogeneous over space. To identify the local COVID-19 characteristics, this study applied the geographically weighted lasso (GWL). GWL provides local regression coefficients, which were used to account for the spatial heterogeneity of SARS-CoV-2 outbreaks. In particular, the GWL pinpoints statistically significant regions with specific local characteristics. The applied explanatory variables involving demographic and socio-economic characteristics that were associated with higher SARS-CoV-2 transmission in the Seoul metropolitan area were as follows: young adults (19~34 years), older population, Christian population, foreign-born population, low-income households, and subway commuters. The COVID-19 case data were classified into three periods: the first period (from January 2020 to July 2021), the second period (from August to November 2020), and the third period (from December 2020 to February 2021), and the GWL was fitted for the entire period (from January 2020 to February 2021). The result showed that young adults, the Christian population, and subway commuters were the most significant local characteristics that influenced SARS-CoV-2 transmissions in the Seoul metropolitan area.
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Affiliation(s)
- Changmin Im
- Department of Geography, Korea University, 145 Anam-ro, Seoul 02841, Korea;
| | - Youngho Kim
- Department of Geography & Geography Education, Korea University, 145 Anam-ro, Seoul 02841, Korea
- Correspondence: ; Tel.: +82-2-3290-2368
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