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PLoS One ; 16(11): e0259706, 2021.
Article in English | MEDLINE | ID: covidwho-1526685

ABSTRACT

BACKGROUND: China is vulnerable to zoonotic disease transmission due to a large agricultural work force, sizable domestic livestock population, and a highly biodiverse ecology. To better address this threat, representatives from the human, animal, and environmental health sectors in China held a One Health Zoonotic Disease Prioritization (OHZDP) workshop in May 2019 to develop a list of priority zoonotic diseases for multisectoral, One Health collaboration. METHODS: Representatives used the OHZDP Process, developed by the US Centers for Disease Control and Prevention (US CDC), to prioritize zoonotic diseases for China. Representatives defined the criteria used for prioritization and determined questions and weights for each individual criterion. A review of English and Chinese literature was conducted prior to the workshop to collect disease specific information on prevalence, morbidity, mortality, and Disability-Adjusted Life Years (DALYs) from China and the Western Pacific Region for zoonotic diseases considered for prioritization. RESULTS: Thirty zoonotic diseases were evaluated for prioritization. Criteria selected included: 1) disease hazard/severity (case fatality rate) in humans, 2) epidemic scale and intensity (in humans and animals) in China, 3) economic impact, 4) prevention and control, and 5) social impact. Disease specific information was obtained from 792 articles (637 in English and 155 in Chinese) and subject matter experts for the prioritization process. Following discussion of the OHZDP Tool output among disease experts, five priority zoonotic diseases were identified for China: avian influenza, echinococcosis, rabies, plague, and brucellosis. CONCLUSION: Representatives agreed on a list of five priority zoonotic diseases that can serve as a foundation to strengthen One Health collaboration for disease prevention and control in China; this list was developed prior to the emergence of SARS-CoV-2 and the COVID-19 pandemic. Next steps focused on establishing a multisectoral, One Health coordination mechanism, improving multisectoral linkages in laboratory testing and surveillance platforms, creating multisectoral preparedness and response plans, and increasing workforce capacity.


Subject(s)
Consensus Development Conferences as Topic , Zoonoses/prevention & control , Animals , China , Humans , Zoonoses/epidemiology , Zoonoses/transmission
2.
MMWR Morb Mortal Wkly Rep ; 69(34): 1166-1169, 2020 Aug 28.
Article in English | MEDLINE | ID: covidwho-732630

ABSTRACT

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22†-July 3, 2020 were analyzed. The analysis was limited to 23 states§ with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.


Subject(s)
Alaskan Natives/statistics & numerical data , Coronavirus Infections/ethnology , Health Status Disparities , Indians, North American/statistics & numerical data , Pneumonia, Viral/ethnology , Adolescent , Adult , Aged , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Child , Child, Preschool , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Female , Humans , Incidence , Infant , Infant, Newborn , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , SARS-CoV-2 , Severity of Illness Index , Treatment Outcome , United States/epidemiology , Young Adult
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