The study on setting priorities of zoonotic agents for medical preparedness and allocation of research resources
The aim of this study is to develop a scoring platform to be used as a reference for both medical preparedness and research resource allocation in the prioritization of zoonoses. Using a case-control design, a comprehensive analysis of 46 zoonoses was conducted to identify factors influencing diseas...
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Published in | PloS one Vol. 19; no. 4; p. e0299527 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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30.04.2024
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Abstract | The aim of this study is to develop a scoring platform to be used as a reference for both medical preparedness and research resource allocation in the prioritization of zoonoses. Using a case-control design, a comprehensive analysis of 46 zoonoses was conducted to identify factors influencing disease prioritization. This analysis provides a basis for constructing models and calculating prioritization scores for different diseases. The case group (n = 23) includes diseases that require immediate notification to health authorities within 24 hours of diagnosis. The control group (n = 23) includes diseases that do not require such immediate notification. Two different models were developed for primary disease prioritization: one model incorporated the four most commonly used prioritization criteria identified through an extensive literature review. The second model used the results of multiple logistic regression analysis to identify significant factors (with p-value less than 0.1) associated with 24-hour reporting, allowing for objective determination of disease prioritization criteria. These different modeling approaches may result in different weights and positive or negative effects of relevant factors within each model. Our study results highlight the variability of zoonotic disease information across time and geographic regions. It provides an objective platform to rank zoonoses and highlights the critical need for regular updates in the prioritization process to ensure timely preparedness. This study successfully established an objective framework for assessing the importance of zoonotic diseases. From a government perspective, it advocates applying principles that consider disease characteristics and medical resource preparedness in prioritization. The results of this study also emphasize the need for dynamic prioritization to effectively improve preparedness to prevent and control disease. |
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AbstractList | The aim of this study is to develop a scoring platform to be used as a reference for both medical preparedness and research resource allocation in the prioritization of zoonoses. Using a case-control design, a comprehensive analysis of 46 zoonoses was conducted to identify factors influencing disease prioritization. This analysis provides a basis for constructing models and calculating prioritization scores for different diseases. The case group (n = 23) includes diseases that require immediate notification to health authorities within 24 hours of diagnosis. The control group (n = 23) includes diseases that do not require such immediate notification. Two different models were developed for primary disease prioritization: one model incorporated the four most commonly used prioritization criteria identified through an extensive literature review. The second model used the results of multiple logistic regression analysis to identify significant factors (with p-value less than 0.1) associated with 24-hour reporting, allowing for objective determination of disease prioritization criteria. These different modeling approaches may result in different weights and positive or negative effects of relevant factors within each model. Our study results highlight the variability of zoonotic disease information across time and geographic regions. It provides an objective platform to rank zoonoses and highlights the critical need for regular updates in the prioritization process to ensure timely preparedness. This study successfully established an objective framework for assessing the importance of zoonotic diseases. From a government perspective, it advocates applying principles that consider disease characteristics and medical resource preparedness in prioritization. The results of this study also emphasize the need for dynamic prioritization to effectively improve preparedness to prevent and control disease. The aim of this study is to develop a scoring platform to be used as a reference for both medical preparedness and research resource allocation in the prioritization of zoonoses. Using a case-control design, a comprehensive analysis of 46 zoonoses was conducted to identify factors influencing disease prioritization. This analysis provides a basis for constructing models and calculating prioritization scores for different diseases. The case group (n = 23) includes diseases that require immediate notification to health authorities within 24 hours of diagnosis. The control group (n = 23) includes diseases that do not require such immediate notification. Two different models were developed for primary disease prioritization: one model incorporated the four most commonly used prioritization criteria identified through an extensive literature review. The second model used the results of multiple logistic regression analysis to identify significant factors (with p-value less than 0.1) associated with 24-hour reporting, allowing for objective determination of disease prioritization criteria. These different modeling approaches may result in different weights and positive or negative effects of relevant factors within each model. Our study results highlight the variability of zoonotic disease information across time and geographic regions. It provides an objective platform to rank zoonoses and highlights the critical need for regular updates in the prioritization process to ensure timely preparedness. This study successfully established an objective framework for assessing the importance of zoonotic diseases. From a government perspective, it advocates applying principles that consider disease characteristics and medical resource preparedness in prioritization. The results of this study also emphasize the need for dynamic prioritization to effectively improve preparedness to prevent and control disease.The aim of this study is to develop a scoring platform to be used as a reference for both medical preparedness and research resource allocation in the prioritization of zoonoses. Using a case-control design, a comprehensive analysis of 46 zoonoses was conducted to identify factors influencing disease prioritization. This analysis provides a basis for constructing models and calculating prioritization scores for different diseases. The case group (n = 23) includes diseases that require immediate notification to health authorities within 24 hours of diagnosis. The control group (n = 23) includes diseases that do not require such immediate notification. Two different models were developed for primary disease prioritization: one model incorporated the four most commonly used prioritization criteria identified through an extensive literature review. The second model used the results of multiple logistic regression analysis to identify significant factors (with p-value less than 0.1) associated with 24-hour reporting, allowing for objective determination of disease prioritization criteria. These different modeling approaches may result in different weights and positive or negative effects of relevant factors within each model. Our study results highlight the variability of zoonotic disease information across time and geographic regions. It provides an objective platform to rank zoonoses and highlights the critical need for regular updates in the prioritization process to ensure timely preparedness. This study successfully established an objective framework for assessing the importance of zoonotic diseases. From a government perspective, it advocates applying principles that consider disease characteristics and medical resource preparedness in prioritization. The results of this study also emphasize the need for dynamic prioritization to effectively improve preparedness to prevent and control disease. |
Audience | Academic |
Author | Chang, Chia-Lin Wei, Sung-Hsi Wang, Kung-Ching Chang, Chao-Chin |
AuthorAffiliation | Guru Angad Dev Veterinary and Animal Sciences University, INDIA 1 Graduate Institute of Microbiology and Public Health, National Chung Hsing University, Taichung, Taiwan, R.O.C 2 Department of Applied Economics, National Chung Hsing University, Taichung, Taiwan, R.O.C 3 Children’s Hospital, China Medical University, Taichung, Taiwan, R.O.C |
AuthorAffiliation_xml | – name: Guru Angad Dev Veterinary and Animal Sciences University, INDIA – name: 3 Children’s Hospital, China Medical University, Taichung, Taiwan, R.O.C – name: 2 Department of Applied Economics, National Chung Hsing University, Taichung, Taiwan, R.O.C – name: 1 Graduate Institute of Microbiology and Public Health, National Chung Hsing University, Taichung, Taiwan, R.O.C |
Author_xml | – sequence: 1 givenname: Kung-Ching orcidid: 0000-0002-7203-9161 surname: Wang fullname: Wang, Kung-Ching – sequence: 2 givenname: Chia-Lin surname: Chang fullname: Chang, Chia-Lin – sequence: 3 givenname: Sung-Hsi surname: Wei fullname: Wei, Sung-Hsi – sequence: 4 givenname: Chao-Chin orcidid: 0000-0002-6299-9214 surname: Chang fullname: Chang, Chao-Chin |
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Cites_doi | 10.3201/eid1804.111151 10.1186/s12889-020-09566-9 10.1371/journal.pone.0025691 10.1016/j.prevetmed.2015.05.006 10.1111/zph.12214 10.1017/S0950268814002246 10.1016/B978-012373944-5.00213-3 10.3201/eid2409.171427 10.1371/journal.pone.0151394 10.1038/nature06536 10.1371/journal.pone.0013965 10.1371/journal.pone.0041590 10.1371/journal.pone.0161576 10.3855/jidc.6582 10.1371/journal.pone.0136353 10.1016/j.onehlt.2018.08.001 10.1590/S1020-49892013000500002 10.1371/journal.pone.0220152 10.1186/1746-6148-8-168 10.1371/journal.pone.0196799 10.2807/1560-7917.ES2014.19.15.20770 10.1371/journal.pone.0068338 10.1016/j.antiviral.2018.09.009 10.2807/ese.13.40.18996-en 10.3390/ijerph13040419 10.1089/fpd.2009.0291 |
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SubjectTerms | Animals Biology and Life Sciences Case-Control Studies Development and progression Evaluation Health Priorities Humans Infection control Lassa fever Logistic Models Medical research Medicine and Health Sciences Medicine, Experimental People and Places Prevention Public health administration Resource Allocation Zoonoses Zoonoses - epidemiology Zoonoses - prevention & control Zoonoses - transmission |
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Title | The study on setting priorities of zoonotic agents for medical preparedness and allocation of research resources |
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