1
|
Shi K, Liu C, Zhong X. Scaling features in high-concentrations PM 2.5 evolution: the Ignored factor affecting scarlet fever incidence. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:217. [PMID: 38849621 DOI: 10.1007/s10653-024-01989-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/06/2024] [Indexed: 06/09/2024]
Abstract
As an acute respiratory disease, scarlet fever has great harm to public health. Some evidence indicates that the time distribution pattern of heavy PM2.5 pollution occurrence may have an impact on health risks. This study aims to reveal the relation between scaling features in high-concentrations PM2.5 (HC-PM2.5) evolution and scarlet fever incidence (SFI). Based on the data of Hong Kong from 2012 to 2019, fractal box-counting dimension (D) is introduced to capture the scaling features of HC-PM2.5. It has been found that index D can quantify the time distribution of HC-PM2.5, and lower D values indicate more cluster distribution of HC-PM2.5. Moreover, scale-invariance in HC-PM2.5 at different time scales has been discovered, which indicates that HC-PM2.5 occurrence is not random but follows a typical power-law distribution. Next, the exposure-response relationship between SFI and scale-invariance in HC-PM2.5 is explored by Distributed lag non-linear model, in conjunction with meteorological factors. It has been discovered that scale-invariance in HC-PM2.5 has a nonlinear effect on SFI. Low and moderate D values of HC-PM2.5 are identified as risk factors for SFI at small time-scale. Moreover, relative risk shows a decreasing trend with the increase of exposure time. These results suggest that exposure to short-term clustered HC-PM2.5 makes individual more prone to SFI than exposure to long-term uniform HC-PM2.5. This means that individuals in slightly-polluted regions may face a greater risk of SFI, once the PM2.5 concentration keeps rising. In the future, it is expected that the relative risk of scarlet fever for a specific region can be estimated based on the quantitative analysis of scaling features in high-concentrations PM2.5 evolution.
Collapse
Affiliation(s)
- Kai Shi
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China
- Key Laboratory of Nanchong City of Ecological Environment Protection and Pollution Prevention in Jialing River Basin, China West Normal University, Nanchong, China
| | - Chunqiong Liu
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China.
- Key Laboratory of Nanchong City of Ecological Environment Protection and Pollution Prevention in Jialing River Basin, China West Normal University, Nanchong, China.
| | - Xinyu Zhong
- College of Mathematics and Statistics, Jishou University, Jishou, Hunan, China.
| |
Collapse
|
2
|
Shang W, Cao G, Wu Y, Kang L, Wang Y, Gao P, Liu J, Liu M. Spatiotemporal cluster of mpox in men who have sex with men: A modeling study in 83 countries. J Med Virol 2023; 95:e29166. [PMID: 37822046 DOI: 10.1002/jmv.29166] [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: 06/29/2023] [Revised: 09/11/2023] [Accepted: 09/30/2023] [Indexed: 10/13/2023]
Abstract
Mpox outbroke globally during 2022-2023, with more than 90% of cases occurring in men who have sex with men (MSM). However, the spatiotemporal distribution of mpox is not well established yet. This study aimed to explore the spatiotemporal clustering of mpox cases in MSM worldwide. We obtained the numbers of mpox cases from Our World in Data, the number of MSM from the Joint United Nations Programme on HIV/AIDS (UNAIDS), UNAIDS DATA 2021 and UNAIDS Global AIDS Update 2022 and literature. We evaluated the spatiotemporal cluster of mpox in MSM using retrospective space-time analyses method. The total number of mpox cases was 85 795 during May 1, 2022 to March 31, 2023. The most likely cluster was Spain (likelihood ratio = 4764.97; p < 0.001), with a cluster period from July 26 to August 14, 2022. There were 11 secondary clusters, which included 46 countries located in western Europe, eastern and northern South America, northern Europe, Canada, Central Africa, southern and central Europe, Latin America, Turkey, Dominican Republic, New Zealand, and Australia. The findings may inform current and future control strategies of mpox and might provide references for the identification of the spatiotemporal distribution of new and emerging infectious diseases in specific populations.
Collapse
Affiliation(s)
- Weijing Shang
- School of Public Health, Peking University, Beijing, China
| | - Guiying Cao
- School of Public Health, Peking University, Beijing, China
| | - Yu Wu
- School of Public Health, Peking University, Beijing, China
| | - Liangyu Kang
- School of Public Health, Peking University, Beijing, China
| | - Yaping Wang
- School of Public Health, Peking University, Beijing, China
| | - Peng Gao
- School of Public Health, Peking University, Beijing, China
| | - Jue Liu
- School of Public Health, Peking University, Beijing, China
| | - Min Liu
- School of Public Health, Peking University, Beijing, China
| |
Collapse
|
3
|
Yu W, Guo L, Shen X, Wang Z, Cai J, Liu H, Mao L, Yao W, Sun Y. Epidemiological characteristics and spatiotemporal clustering of scarlet fever in Liaoning Province, China, 2010-2019. Acta Trop 2023; 245:106968. [PMID: 37307889 DOI: 10.1016/j.actatropica.2023.106968] [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: 05/08/2023] [Revised: 06/08/2023] [Accepted: 06/10/2023] [Indexed: 06/14/2023]
Abstract
BACKGROUND To explore the epidemiological characteristics and spatiotemporal distribution of scarlet fever in Liaoning Province, which could provide scientific evidence for the formulation and improvement of prevention and control strategies and measures. METHODS Data on scarlet fever cases and population were obtained from the China Information System for Disease Control and Prevention in Liaoning Province between 2010 and 2019. We examined the spatial and spatiotemporal clusters of scarlet fever across Liaoning Province using the Moran's I, local indicators of spatial association, local Gi* hotspot statistics, and Kulldorff's retrospective space-time scan statistical analysis. RESULTS Between 1st January 2010 and 31st December 2019, 46,652 cases of scarlet fever were reported in Liaoning Province, with an annual average incidence of 10.67 per 100,000. The incidence of scarlet fever had obvious seasonality with high incidence in early summer June and early winter December. The male-to-female ratio was 1.53:1. The highest incidence of cases occurred in 3-9 year old children. The most likely spatiotemporal cluster and the secondary clusters were detected in urban regions of Shenyang and Dalian, Liaoning Province. CONCLUSIONS The incidence of scarlet fever has obvious spatiotemporal clustering, with the high-risk areas mainly concentrated in urban area of Shenyang and Dalian, Liaoning Province. Control strategies need to focus on high-risk season, high-risk areas and high-risk populations in order to reduce the incidence of scarlet fever.
Collapse
Affiliation(s)
- Weijun Yu
- Institute for Prevention and Control of Infection and Infectious Diseases, Liaoning Provincial Center for Disease Control and Prevention, No.168, Jin Feng Street, Shenyang, Liaoning 110172, China
| | - Lining Guo
- Hunnan District Center for Disease Control and Prevention, Shenyang, Liaoning 110015, China
| | - Xiulian Shen
- Epidemic Surveillance/Public Health Emergency Response Center, Yunnan Provincial Center for Disease Control and Prevention, Kunming, Yunnan 650022, China
| | - Zijiang Wang
- Institute for Prevention and Control of Infection and Infectious Diseases, Liaoning Provincial Center for Disease Control and Prevention, No.168, Jin Feng Street, Shenyang, Liaoning 110172, China; Department of Emergency Management, Liaoning Provincial Center for Disease Control and Prevention, No.168, Jin Feng Street, Shenyang, Liaoning 110172, China.
| | - Jian Cai
- Department of Communicable Disease Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Huihui Liu
- Chinese Field Epidemiology Training Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Lingling Mao
- Institute for Prevention and Control of Infection and Infectious Diseases, Liaoning Provincial Center for Disease Control and Prevention, No.168, Jin Feng Street, Shenyang, Liaoning 110172, China
| | - Wenqing Yao
- Institute for Prevention and Control of Infection and Infectious Diseases, Liaoning Provincial Center for Disease Control and Prevention, No.168, Jin Feng Street, Shenyang, Liaoning 110172, China
| | - Yingwei Sun
- Institute for Prevention and Control of Infection and Infectious Diseases, Liaoning Provincial Center for Disease Control and Prevention, No.168, Jin Feng Street, Shenyang, Liaoning 110172, China.
| |
Collapse
|
4
|
Cui J, Zhang Y, Ge H, Cao Y, Su X. Patterns in the Incidence of Scarlet Fever Among Children Aged 0-9 Years - China, 2010-2019. China CDC Wkly 2023; 5:756-762. [PMID: 37692760 PMCID: PMC10485360 DOI: 10.46234/ccdcw2023.143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023] Open
Abstract
Introduction This study investigates the patterns of scarlet fever among Chinese children aged 0-9 years from 2010 to 2019. The objective is to provide insights that may inform potential adjustments to China's current prevention and control tactics for this illness. Methods The present study utilized data on the occurrence of scarlet fever in children from 2010 to 2019, sourced from the National Notifiable Disease Reporting System database, managed by the Chinese Center for Disease Control and Prevention. This research implemented SAS9.4 software to construct trajectory models representing the temporal incidence of scarlet fever, accounting for key variables such as sex, geographic region, urban versus rural dwellings, and various age brackets. Results From 2010 to 2019, a total of 554,695 scarlet fever cases were reported among children aged 0-9 years in the 31 mainland Chinese provincial-level administrative divisions, signifying a rate of 35.36 per 100,000 individuals. An inconsistent yet generally rising trend was observed, evidenced by a 3.17-fold increase in reported cases and a 3.02-fold escalation in incidence rate over this period. Examination of these trends revealed three distinctive developmental patterns for both males and females, with the lowest prevalence in the first trajectory and the highest in the third. The incidence was consistently higher among males than females in all trajectories. The urban and northern regions displayed equal or greater trajectory rates than their rural and southern counterparts, respectively. In terms of age groups, the lowest incidence was observed in the 0-1-year age group, while the highest was recorded in the 4-5 and 6-7-year age groups. Conclusions Between 2010 and 2019, there was a marked increase in the incidence of scarlet fever among children in China. The disease predominantly impacts urban-dwelling children, ranging from 4 to 7 years old, in the northern regions of the country. The incidence is reported to be higher among boys compared to girls.
Collapse
Affiliation(s)
- Jinyu Cui
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yewu Zhang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hui Ge
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Cao
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xuemei Su
- Chinese Center for Disease Control and Prevention, Beijing, China
| |
Collapse
|
5
|
Lu JW, Mao JJ, Zhang RR, Li CH, Sun Y, Xu WQ, Zhuang X, Zhang B, Qin G. Association between long-term exposure to ambient air pollutants and the risk of tuberculosis: A time-series study in Nantong, China. Heliyon 2023; 9:e17347. [PMID: 37441410 PMCID: PMC10333459 DOI: 10.1016/j.heliyon.2023.e17347] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 06/01/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023] Open
Abstract
Background Increasing evidence has shown that the risk of tuberculosis (TB) might be related to the exposure to air pollutants; however, the findings are inconsistent and studies on long-term air pollutant exposure and TB risk are scarce. This study aime to assess the relationship between monthly exposure to air pollution and TB risk in Nantong, China. Methods We collected the time series data on the number of TB cases, as well as environmental and socioeconomic covariates from January 2005 to December 2020. The impact of air pollutant exposure on TB risk was evaluated using the distributed lag nonlinear model (DLNM). Stratified analyses were conducted to examine the effect modifications of sex and age on the association between air pollutants and TB risk. Sensitivity analyses were applied to test the stability of the model. Results There were a total of 54,096 cases of TB in Nantong during the study period. In the single-pollutant model, for each 10 μg/m3 increase in concentration, the pooled relative risks (RRs) of TB reached the maximum to 1.10 (95% confidence interval (CI): 1.04-1.16, lag 10 months) for particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5), 1.05 (95% CI: 1.01-1.10, lag 9 months) for particulate matter with aerodynamic diameter less than 10 μm (PM10), and 1.11 (95%CI: 1.04-1.19, lag 10 months) for nitrogen dioxide (NO2). Ozone (O3) did not show significant effect on TB risk. Effect modifications of sex and age on the association between air pollutants and TB risk were not observed. The multi-pollutant model results showed no significant variation compared with the single-pollutant model. Conclusions Our study suggests that air pollutants pose a substantial threat to the TB risk. Reducing air pollution might be crucial for TB prevention and control.
Collapse
Affiliation(s)
- Jia-Wang Lu
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
| | - Jun-Jie Mao
- Department of Epidemiology and Biostatistics, Nantong University School of Public Health, Nantong, China
| | - Rong-Rong Zhang
- Nantong Centre for Disease Control and Prevention, Nantong, China
| | - Chun-Hu Li
- Department of Epidemiology and Biostatistics, Nantong University School of Public Health, Nantong, China
| | - Yu Sun
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
| | - Wan-Qing Xu
- Department of Internal Medicine, Nantong University Medical School, Nantong, China
| | - Xun Zhuang
- Department of Epidemiology and Biostatistics, Nantong University School of Public Health, Nantong, China
| | - Bin Zhang
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
| | - Gang Qin
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
- National Key Clinical Construction Specialty - Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Nantong University, Nantong, China
| |
Collapse
|
6
|
Fu Y, Wang W. Association between provincial sunshine duration and mortality rates in China: Panel data study. Heliyon 2023; 9:e15862. [PMID: 37215780 PMCID: PMC10199197 DOI: 10.1016/j.heliyon.2023.e15862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 03/09/2023] [Accepted: 04/24/2023] [Indexed: 05/24/2023] Open
Abstract
Background mortality rates are usually influenced by the variations of environmental factors. However, there are few studies on the impact of sunlight duration induced mortality. In this study, we examine provincial level associations between the sunshine duration and crude mortality rates. Methods we use China mortality data from the National Bureau of Statistics of China combined with China census data and data from the China Meteorological Data Service Centre. Annual mortality rates for 31 provinces, autonomous regions, and municipalities in China from 2005 to 19. Data are analyzed at the provincial level by using panel regression methods. The main outcome measures are the mortality rates associated with average daily sunshine duration. Then we perform a series of sentimental analyses. Results the average daily sunshine duration ratio cubed is positively associated with provincial level mortality rates (β = 11.509, 95% confidence interval 1.869 to 21.148). According to this estimate, increasing 2.895 h of additional daily sunshine is associated with an estimated 1.15% increase in the crude mortality rates. A series of sensitivity analyses show a consistent pattern of associations between average daily sunshine duration ratio cubed and mortality rates. Conclusions more sunshine duration is associated with increased mortality rates. While the associations documented cannot be assumed to be causal, they suggest a potential association between increased sunshine duration and increased mortality rates.
Collapse
Affiliation(s)
- Yu Fu
- Urban Vocational College of Sichuan, Chengdu, China
| | - Weidong Wang
- Sichuan Cancer Hospital & Institute, Chengdu, China
| |
Collapse
|
7
|
Ma Y, Gao S, Kang Z, Shan L, Jiao M, Li Y, Liang L, Hao Y, Zhao B, Ning N, Gao L, Cui Y, Sun H, Wu Q, Liu H. Epidemiological trend in scarlet fever incidence in China during the COVID-19 pandemic: A time series analysis. Front Public Health 2022; 10:923318. [PMID: 36589977 PMCID: PMC9799716 DOI: 10.3389/fpubh.2022.923318] [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: 04/19/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
Objective Over the past decade, scarlet fever has caused a relatively high economic burden in various regions of China. Non-pharmaceutical interventions (NPIs) are necessary because of the absence of vaccines and specific drugs. This study aimed to characterize the demographics of patients with scarlet fever, describe its spatiotemporal distribution, and explore the impact of NPIs on the disease in the era of coronavirus disease 2019 (COVID-19) in China. Methods Using monthly scarlet fever data from January 2011 to December 2019, seasonal autoregressive integrated moving average (SARIMA), advanced innovation state-space modeling framework that combines Box-Cox transformations, Fourier series with time-varying coefficients, and autoregressive moving average error correction method (TBATS) models were developed to select the best model for comparing between the expected and actual incidence of scarlet fever in 2020. Interrupted time series analysis (ITSA) was used to explore whether NPIs have an effect on scarlet fever incidence, while the intervention effects of specific NPIs were explored using correlation analysis and ridge regression methods. Results From 2011 to 2017, the total number of scarlet fever cases was 400,691, with children aged 0-9 years being the main group affected. There were two annual incidence peaks (May to June and November to December). According to the best prediction model TBATS (0.002, {0, 0}, 0.801, {<12, 5>}), the number of scarlet fever cases was 72,148 and dual seasonality was no longer prominent. ITSA showed a significant effect of NPIs of a reduction in the number of scarlet fever episodes (β2 = -61526, P < 0.005), and the effect of canceling public events (c3) was the most significant (P = 0.0447). Conclusions The incidence of scarlet fever during COVID-19 was lower than expected, and the total incidence decreased by 80.74% in 2020. The results of this study indicate that strict NPIs may be of potential benefit in preventing scarlet fever occurrence, especially that related to public event cancellation. However, it is still important that vaccines and drugs are available in the future.
Collapse
Affiliation(s)
- Yunxia Ma
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Shanshan Gao
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Zheng Kang
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Linghan Shan
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Mingli Jiao
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Ye Li
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Libo Liang
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Yanhua Hao
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Binyu Zhao
- Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, China
| | - Ning Ning
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Lijun Gao
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Yu Cui
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Hong Sun
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China
| | - Qunhong Wu
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China,*Correspondence: Qunhong Wu
| | - Huan Liu
- Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, China,Huan Liu
| |
Collapse
|
8
|
Wen L, Yang D, Li Y, Lu D, Su H, Tang M, Song X. Spatial Effect of Ecological Environmental Factors on Mumps in China during 2014-2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15429. [PMID: 36497504 PMCID: PMC9735526 DOI: 10.3390/ijerph192315429] [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: 09/17/2022] [Revised: 11/17/2022] [Accepted: 11/17/2022] [Indexed: 06/17/2023]
Abstract
(1) Background: although mumps vaccines have been introduced in most countries around the world in recent years, mumps outbreaks have occurred in countries with high vaccination rates. At present, China remains the focus of the global fight against mumps. This study aims to observe the epidemic characteristics and spatial clustering patterns of mumps and to investigate the potential factors affecting the disease incidence, which could provide novel ideas and avenues for future research as well as the prevention and control of mumps. (2) Methods: we used ArcGIS software to visualize the spatial distribution and variation of mumps. Spatial autocorrelation analysis was applied to detect the spatial dependence and clustering patterns of the incidence. We applied the Spatial Durbin Panel Model (SDPM) to explore the spatial associations of ecological environmental factors with mumps. (3) Results: overall, the incidence rate showed a significant upward trend from 2014 to 2018, with the highest number of cases in the 10-15-year age group and from May to June. Geographically, the high incidence clusters were concentrated in southern regions, including Hunan, Hubei, Chongqing, Guizhou, Guangdong, and Guangxi. This study also found that mumps has a positive spatial spillover effect in the study area. The average temperature and GDP of the local and adjacent areas have a significant impact on mumps. The increase in PM2.5 contributes to the rise in the incidence of mumps in this region. (4) Conclusions: these results can offer some novel ideas for policymakers and researchers. Local meteorological conditions and economic levels can extend to surrounding areas to affect the occurrence of mumps, so regional cooperation becomes particularly important. We recommend investment of public health funds in areas with a high incidence of mumps and developing economies to reduce and control the incidence of mumps.
Collapse
Affiliation(s)
- Li Wen
- Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Danling Yang
- Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Yanning Li
- Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Dongjia Lu
- Guangxi Key Laboratory of AIDS Prevention and Treatment, Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, Nanning 530021, China
| | - Haixia Su
- Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Mengying Tang
- Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Xiaokun Song
- Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
| |
Collapse
|
9
|
Spatiotemporal dynamics and potential ecological drivers of acute respiratory infectious diseases: an example of scarlet fever in Sichuan Province. BMC Public Health 2022; 22:2139. [PMID: 36411416 PMCID: PMC9680133 DOI: 10.1186/s12889-022-14469-y] [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: 05/05/2022] [Accepted: 10/17/2022] [Indexed: 11/23/2022] Open
Abstract
OBJECT Scarlet fever is an acute respiratory infectious disease that endangers public health and imposes a huge economic burden. In this paper, we systematically studied its spatial and temporal evolution and explore its potential ecological drivers. The goal of this research is to provide a reference for analysis based on surveillance data of scarlet fever and other acute respiratory infectious illnesses, and offer suggestions for prevention and control. METHOD This research is based on a spatiotemporal multivariate model (Endemic-Epidemic model). Firstly, we described the epidemiology status of the scarlet fever epidemic in Sichuan Province from 2016 to 2019. Secondly, we used spatial autocorrelation analysis to understand the spatial pattern. Thirdly, we applied the endemic-epidemic model to analyze the spatiotemporal dynamics by quantitatively decomposing cases into endemic, autoregressive, and spatiotemporal components. Finally, we explored potential ecological drivers that could influence the spread of scarlet fever. RESULTS From 2016 to 2019, the incidence of scarlet fever in Sichuan Province varied much among cities. In terms of temporal distribution, there were 1-2 epidemic peaks per year, and they were mainly concentrated from April to June and October to December. In terms of transmission, the endemic and temporal spread were predominant. Our findings imply that the school holiday could help to reduce the spread of scarlet fever, and a standard increase in Gross Domestic Product (GDP) was associated with 2.6 folds contributions to the epidemic among cities. CONCLUSION Scarlet fever outbreaks are more susceptible to previous cases, as temporal spread accounted for major transmission in many areas in Sichuan Province. The school holidays and GDP can influence the spread of infectious diseases. Given that covariates could not fully explain heterogeneity, adding random effects was essential to improve accuracy. Paying attention to critical populations and hotspots, as well as understanding potential drivers, is recommended for acute respiratory infections such as scarlet fever. For example, our study reveals GDP is positively associated with spatial spread, indicating we should consider GDP as an important factor when analyzing the potential drivers of acute infectious disease.
Collapse
|
10
|
Qian L, Wang Y, Wei X, Liu P, Magalhaes RJS, Qian Q, Peng H, Wen L, Xu Y, Sun H, Yin W, Zhang W. Epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province during 2012–2020. PLoS Negl Trop Dis 2022; 16:e0010278. [PMID: 36174105 PMCID: PMC9553047 DOI: 10.1371/journal.pntd.0010278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 10/11/2022] [Accepted: 09/13/2022] [Indexed: 12/02/2022] Open
Abstract
Background Scrub typhus has become a serious public health concern in the Asia-Pacific region including China. There were new natural foci continuously recognized and dramatically increased reported cases in mainland China. However, the epidemiological characteristics and spatiotemporal patterns of scrub typhus in Fujian province have yet to be investigated. Objective This study proposes to explore demographic characteristics and spatiotemporal dynamics of scrub typhus cases in Fujian province, and to detect high-risk regions between January 2012 and December 2020 at county/district scale and thereby help in devising public health strategies to improve scrub typhus prevention and control measures. Method Monthly cases of scrub typhus reported at the county level in Fujian province during 2012–2020 were collected from the National Notifiable Disease Surveillance System. Time-series analyses, spatial autocorrelation analyses and space-time scan statistics were applied to identify and visualize the spatiotemporal patterns of scrub typhus cases in Fujian province. The demographic differences of scrub typhus cases from high-risk and low-risk counties in Fujian province were also compared. Results A total of 11,859 scrub typhus cases reported in 87 counties from Fujian province were analyzed and the incidence showed an increasing trend from 2012 (2.31 per 100,000) to 2020 (3.20 per 100,000) with a peak in 2018 (4.59 per 100,000). There existed two seasonal peaks in June-July and September-October every year in Fujian province. A significant positive spatial autocorrelation of scrub typhus incidence in Fujian province was observed with Moran’s I values ranging from 0.258 to 0.471 (P<0.001). Several distinct spatiotemporal clusters mainly concentrated in north and southern parts of Fujian province. Compared to low-risk regions, a greater proportion of cases were female, farmer, and older residents in high-risk counties. Conclusions These results demonstrate a clear spatiotemporal heterogeneity of scrub typhus cases in Fujian province, and provide the evidence in directing future researches on risk factors and effectively assist local health authorities in the refinement of public health interventions against scrub typhus transmission in the high risk regions. Scrub typhus is a vector-borne zoonotic disease caused by Orientia tsutsugamushi and is popular in the Asia-Pacific area. Nowadays scrub typhus has been recognized as a considerable burden on public health in Fujian province. We explored the epidemiological characteristics, spatiotemporal patterns and diffusion characteristics of scrub typhus, and detected high-risk regions at the county level in Fujian province between January 2012 and December 2020. Our results indicated that the majority of cases were reported in June-July and September-October and that that middle aged and elderly people were more prone to infection every year in Fujian province. The spatial autocorrelation analysis revealed clustering in geographic distribution of cases and several distinct spatiotemporal clusters were identified in north and southern parts of Fujian province. Compared with cases from low-risk areas, a higher proportion of cases were female, farmer, and older residents in high-risk counties.
Collapse
Affiliation(s)
- Li Qian
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, Chongqing, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yong Wang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Ping Liu
- Department of General Practice, Chinese PLA General Hospital-Sixth Medical Center, Beijing, China
| | - Ricardo J. Soares Magalhaes
- Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Brisbane, Australia
- Child Health Research Center, The University of Queensland, Brisbane, Australia
| | - Quan Qian
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hong Peng
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Liang Wen
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hailong Sun
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenwu Yin
- Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (WZ)
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (WZ)
| |
Collapse
|
11
|
Wang R, Li X, Hu Z, Jing W, Zhao Y. Spatial Heterogeneity and Its Influencing Factors of Syphilis in Ningxia, Northwest China, from 2004 to 2017: A Spatial Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10541. [PMID: 36078254 PMCID: PMC9518519 DOI: 10.3390/ijerph191710541] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/20/2022] [Accepted: 08/22/2022] [Indexed: 06/15/2023]
Abstract
Syphilis remains a growing and resurging infectious disease in China. However, exploring the influence of environmental factors on the spatiotemporal distribution of syphilis remains under explore. This study aims to analyze the spatiotemporal distribution characteristics of syphilis in Ningxia, Northwest China, and its potential environmental influencing factors. Based on the standardized incidence ratio of syphilis for 22 administrative areas in Ningxia from 2004 to 2017, spatiotemporal autocorrelation and scan analyses were employed to analyze the spatial and temporal distribution characteristics of syphilis incidence, while a fixed-effect spatial panel regression model identified the potential factors affecting syphilis incidence. Syphilis incidence increased from 3.78/100,000 in 2004 to 54.69/100,000 in 2017 with significant spatial clustering in 2007 and 2009-2013. The "high-high" and "low-low" clusters were mainly distributed in northern and southern Ningxia, respectively. The spatial error panel model demonstrated that the syphilis incidence may be positively correlated with the per capita GDP and tertiary industry GDP and negatively correlated with the number of health facilities and healthcare personnel. Sex ratio and meteorological factors were not significantly associated with syphilis incidence. These results show that the syphilis incidence in Ningxia is still increasing and has significant spatial distribution differences and clustering. Socio-economic and health-resource factors could affect the incidence; therefore, strengthening syphilis surveillance of migrants in the economically developed region and allocating health resources to economically underdeveloped areas may effectively help prevent and control syphilis outbreaks in high-risk cluster areas of Ningxia.
Collapse
Affiliation(s)
- Ruonan Wang
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, 1160 Shengli Street, Xingqing District, Yinchuan 750001, China
| | - Xiaolong Li
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, 1160 Shengli Street, Xingqing District, Yinchuan 750001, China
| | - Zengyun Hu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Wenjun Jing
- School of Statistics, Shanxi University of Finance and Economics, Taiyuan 030006, China
| | - Yu Zhao
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, 1160 Shengli Street, Xingqing District, Yinchuan 750001, China
| |
Collapse
|
12
|
He Y, Ma C, Guo X, Pan J, Xu W, Liu S. Collateral Impact of COVID-19 Prevention Measures on Re-Emergence of Scarlet Fever and Pertussis in Mainland China and Hong Kong China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:9909. [PMID: 36011545 PMCID: PMC9407746 DOI: 10.3390/ijerph19169909] [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: 05/05/2022] [Revised: 08/06/2022] [Accepted: 08/09/2022] [Indexed: 06/15/2023]
Abstract
The incidence of scarlet fever and pertussis has increased significantly in China in recent years. During the COVID-19 pandemic, stringent non-pharmaceutical intervention measures were widely adopted to contain the spread of the virus, which may also have essential collateral impacts on other infectious diseases, such as scarlet fever and pertussis. We compared the incidence data of scarlet fever and pertussis in Mainland China and Hong Kong from 2004 to 2021 before and after the COVID-19 pandemic. The results show that the incidence of both diseases decreased significantly in 2020-2021 compared to the after-re-emergence stage in these two locations. Specifically, in 2020, scarlet fever decreased by 73.13% and pertussis by 76.63% in Mainland China, and 83.70% and 76.10%, respectively, in Hong Kong. In the absence of COVID-19, the predicted incidence of both diseases was much higher than the actual incidence in Mainland China and Hong Kong in 2020-2021. This study demonstrates that non-pharmaceutical measures implemented during the COVID-19 pandemic can partially reduce scarlet fever and pertussis re-emergence in Mainland China and Hong Kong.
Collapse
Affiliation(s)
- Yiran He
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing 100872, China
| | - Chenjin Ma
- College of Statistics and Data Science, Faculty of Science, Beijing University of Technology, Beijing 100124, China
| | - Xiangyu Guo
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing 100872, China
| | - Jinren Pan
- Department of Infectious Diseases, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Wangli Xu
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing 100872, China
| | - Shelan Liu
- Department of Infectious Diseases, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| |
Collapse
|
13
|
Jiang F, Wei T, Hu X, Han Y, Jia J, Pan B, Ni W. The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis. BMC Infect Dis 2021; 21:987. [PMID: 34548016 PMCID: PMC8456591 DOI: 10.1186/s12879-021-06674-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 09/08/2021] [Indexed: 12/16/2022] Open
Abstract
Background We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014–2018. Methods A distributed lag non-linear model (DLNM) combined with a generalized additive mixed model (GAMM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results A total of 6316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different relative risk (RR) of air pollution degrees [1.172, 95% confidence interval (CI): 1.038–1.323 in mild air pollution; 1.374, 95% CI 1.078–1.749 in moderate air pollution; 1.610, 95% CI 1.163–2.314 in severe air pollution; 1.887, 95% CI 1.163–3.061 in most severe air pollution]. Conclusions Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06674-8.
Collapse
Affiliation(s)
- Fachun Jiang
- Department of Acute Infectious Diseases, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Tao Wei
- Qingdao Women and Children's Hospital, Qingdao University, No.6 Tongfu Road, Qingdao City, 266000, Shandong Province, People's Republic of China
| | - Xiaowen Hu
- Department of Acute Infectious Diseases, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Yalin Han
- Department of Acute Infectious Diseases, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Jing Jia
- Department of Acute Infectious Diseases, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Bei Pan
- Department of Acute Infectious Diseases, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Wei Ni
- Qingdao Women and Children's Hospital, Qingdao University, No.6 Tongfu Road, Qingdao City, 266000, Shandong Province, People's Republic of China.
| |
Collapse
|