1
|
Zou F, Xiao J, Jin Y, Jian R, Hu Y, Liang X, Ma W, Zhu S. Multilayer factors associated with excess all-cause mortality during the omicron and non-omicron waves of the COVID-19 pandemic: time series analysis in 29 countries. BMC Public Health 2024; 24:350. [PMID: 38308279 PMCID: PMC10835930 DOI: 10.1186/s12889-024-17803-8] [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: 10/08/2023] [Accepted: 01/18/2024] [Indexed: 02/04/2024] Open
Abstract
BACKGROUND The COVID-19 pandemic has resulted in significant excess mortality globally. However, the differences in excess mortality between the Omicron and non-Omicron waves, as well as the contribution of local epidemiological characteristics, population immunity, and social factors to excess mortality, remain poorly understood. This study aims to solve the above problems. METHODS Weekly all-cause death data and covariates from 29 countries for the period 2015-2022 were collected and used. The Bayesian Structured Time Series Model predicted expected weekly deaths, stratified by gender and age groups for the period 2020-2022. The quantile-based g-computation approach accounted for the effects of factors on the excess all-cause mortality rate. Sensitivity analyses were conducted using alternative Omicron proportion thresholds. RESULTS From the first week of 2021 to the 30th week of 2022, the estimated cumulative number of excess deaths due to COVID-19 globally was nearly 1.39 million. The estimated weekly excess all-cause mortality rate in the 29 countries was approximately 2.17 per 100,000 (95% CI: 1.47 to 2.86). Weekly all-cause excess mortality rates were significantly higher in both male and female groups and all age groups during the non-Omicron wave, except for those younger than 15 years (P < 0.001). Sensitivity analysis confirmed the stability of the results. Positive associations with all-cause excess mortality were found for the constituent ratio of non-Omicron in all variants, new cases per million, positive rate, cardiovascular death rate, people fully vaccinated per hundred, extreme poverty, hospital patients per million humans, people vaccinated per hundred, and stringency index. Conversely, other factors demonstrated negative associations with all-cause excess mortality from the first week of 2021 to the 30th week of 2022. CONCLUSION Our findings indicate that the COVID-19 Omicron wave was associated with lower excess mortality compared to the non-Omicron wave. This study's analysis of the factors influencing excess deaths suggests that effective strategies to mitigate all-cause mortality include improving economic conditions, promoting widespread vaccination, and enhancing overall population health. Implementing these measures could significantly reduce the burden of COVID-19, facilitate coexistence with the virus, and potentially contribute to its elimination.
Collapse
Affiliation(s)
- Fengjuan Zou
- Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, 511430, China
| | - Yingying Jin
- Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China
| | - Ronghua Jian
- Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China
| | - Yijun Hu
- Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China
| | - Xiaofeng Liang
- Disease Control and Prevention Institute, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China
- Chinese Preventive Medicine Association, Beijing, 100062, China
| | - Wenjun Ma
- Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
| | - Sui Zhu
- Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
| |
Collapse
|
2
|
He CQ, Sun BH, Yu WT, An SY, Qiao BJ, Wu W. Evaluating the impact of COVID-19 outbreak on hepatitis B and forecasting the epidemiological trend in mainland China: a causal analysis. BMC Public Health 2024; 24:47. [PMID: 38166922 PMCID: PMC10763123 DOI: 10.1186/s12889-023-17587-3] [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: 03/20/2023] [Accepted: 12/26/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND It is uncertain how COVID-19 outbreak influences the hepatitis B epidemics. This study aims to evaluate the effects on hepatitis B owing to the COVID-19 outbreak and forecast the hepatitis B epidemiological trend in mainland China to speed up the course of the "End viral hepatitis Strategy". METHODS We estimated the causal impacts and created a forecast through adopting monthly notifications of hepatitis B each year from 2005 to 2020 in mainland China using the Bayesian structural time series (BSTS) method. RESULTS The hepatitis B epidemics fluctuates irregularly during the period 2005-2007(APC = 8.7, P = 0.246) and 2015-2020(APC = 1.7, P = 0.290), and there is a downturn (APC=-3.2, 95% CI -5.2 to -1.2, P = 0.006) from 2007 to 2015 in mainland China. The COVID-19 outbreak was found to have a monthly average reduction on the hepatitis B epidemics of 26% (95% CI 18-35%) within the first three months in 2020,17% (95% CI 7.7-26%) within the first six months in 2020, and 10% (95% CI19-22%) all year as a result of the COVID-19 outbreak, (probability of causal effect = 96.591%, P = 0.034) and the forecasts showed an upward trend from 2021 to 2025 (annual percentage change = 4.18, 95% CI 4.0 to 4.3, P < 0.001). CONCLUSION The COVID-19 has a positive effect on the decline of hepatitis B cases. And the potential of BSTS model to forecast the epidemiological trend of the hepatitis B can be applied in automatic public health policymaking in mainland China.
Collapse
Affiliation(s)
- Chao-Qun He
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Bai-Hong Sun
- Liaoning Provincial Centers for Disease Control and Prevention, Shenyang, Liaoning, China
| | - Wang-Tao Yu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Shu-Yi An
- Liaoning Provincial Centers for Disease Control and Prevention, Shenyang, Liaoning, China
| | - Bao-Jun Qiao
- Liaoning Provincial Centers for Disease Control and Prevention, Shenyang, Liaoning, China
| | - Wei Wu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.
| |
Collapse
|
3
|
Yaladanda N, Mopuri R, Vavilala H, Bhimala KR, Gouda KC, Kadiri MR, Upadhyayula SM, Mutheneni SR. The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:59194-59211. [PMID: 36997790 DOI: 10.1007/s11356-023-26672-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/23/2023] [Indexed: 05/10/2023]
Abstract
The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively. The nonlinear associations between individual and synergistic effect of meteorological factors and malaria cases were assessed, and climate-based malaria prediction models were developed using the generalized additive model (GAM) with Gaussian distribution. During the study period, a total of 216,943 and 125,926 cases were recorded in Meghalaya and Tripura, respectively, and majority of the cases occurred due to the infection of Plasmodium falciparum in both the states. The temperature and relative humidity in Meghalaya and temperature, rainfall, relative humidity, and soil moisture in Tripura showed a significant nonlinear effect on malaria; moreover, the synergistic effects of temperature and relative humidity (SI=2.37, RERI=0.58, AP=0.29) and temperature and rainfall (SI=6.09, RERI=2.25, AP=0.61) were found to be the key determinants of malaria transmission in Meghalaya and Tripura, respectively. The developed climate-based malaria prediction models are able to predict the malaria cases accurately in both Meghalaya (RMSE: 0.0889; R2: 0.944) and Tripura (RMSE: 0.0451; R2: 0.884). The study found that not only the individual climatic factors can significantly increase the risk of malaria transmission but also the synergistic effects of climatic factors can drive the malaria transmission multifold. This reminds the policymakers to pay attention to the control of malaria in situations with high temperature and relative humidity and high temperature and rainfall in Meghalaya and Tripura, respectively.
Collapse
Affiliation(s)
- Nikhila Yaladanda
- EIACP Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, Telangana, 500007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Rajasekhar Mopuri
- EIACP Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, Telangana, 500007, India
| | - Hariprasad Vavilala
- EIACP Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, Telangana, 500007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Kantha Rao Bhimala
- CSIR-Fourth Paradigm Institute, NAL Belur Campus, Bangalore, Karnataka, 560037, India
| | - Krushna Chandra Gouda
- CSIR-Fourth Paradigm Institute, NAL Belur Campus, Bangalore, Karnataka, 560037, India
| | - Madhusudhan Rao Kadiri
- EIACP Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, Telangana, 500007, India
| | - Suryanarayana Murty Upadhyayula
- National Institute of Pharmaceutical Education and Research (NIPER), Sila Katamur, Halugurisuk, Changsari, Kamrup, Assam, 781101, India
| | - Srinivasa Rao Mutheneni
- EIACP Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, Telangana, 500007, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
| |
Collapse
|
4
|
Drews SJ, Wendel S, Leiby DA, Tonnetti L, Ushiro-Lumb I, O'Brien SF, Lieshout-Krikke RW, Bloch EM. Climate change and parasitic risk to the blood supply. Transfusion 2023; 63:638-645. [PMID: 36565251 DOI: 10.1111/trf.17234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 12/02/2022] [Accepted: 12/04/2022] [Indexed: 12/25/2022]
Affiliation(s)
- Steven J Drews
- Canadian Blood Services, Microbiology, Donation Policy and Studies, Edmonton, Alberta, Canada
- Division of Diagnostic and Applied Microbiology, Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Silvano Wendel
- Blood Bank, Hospital Sírio-Libanês Blood Bank, São Paulo, Brazil
| | - David A Leiby
- Department of Microbiology, Immunology, & Tropical Medicine, George Washington University, Washington, DC, USA
| | - Laura Tonnetti
- American Red Cross, Scientific Affairs, Holland Laboratories for the Biomedical Sciences, Rockville, Maryland, USA
| | | | - Sheila F O'Brien
- Canadian Blood Services, Epidemiology and Surveillance, Microbiology, Ottawa, Ontario, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Ryanne W Lieshout-Krikke
- Department of Medical Affairs, Corporate Staff, Sanquin Blood Supply Foundation, Amsterdam, the Netherlands
| | - Evan M Bloch
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|