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SARS-CoV-2 transmission potential and rural-urban disease burden disparities across Alabama, Louisiana, and Mississippi, March 2020 - May 2021. Ann Epidemiol 2022; 71:1-8. [PMID: 35472488 PMCID: PMC9035618 DOI: 10.1016/j.annepidem.2022.04.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 03/19/2022] [Accepted: 04/15/2022] [Indexed: 11/17/2022]
Abstract
PURPOSE To quantify and compare SARS-CoV-2 transmission potential across Alabama, Louisiana, and Mississippi and selected counties. METHODS To determine the time-varying reproduction number Rt of SARS-CoV-2, we applied the R package EpiEstim to the time series of daily incidence of confirmed cases (mid-March 2020 - May 17, 2021) shifted backward by 9 days. Median Rt percentage change when policies changed was determined. Linear regression was performed between log10-transformed cumulative incidence and log10-transformed population size at four time points. RESULTS Stay-at-home orders, face mask mandates, and vaccinations were associated with the most significant reductions in SARS-CoV-2 transmission in the three southern states. Rt across the three states decreased significantly by ≥20% following stay-at-home orders. We observed varying degrees of reductions in Rt across states following other policies. Rural Alabama counties experienced higher per capita cumulative cases relative to urban ones as of June 17 and October 17, 2020. Meanwhile, Louisiana and Mississippi saw the disproportionate impact of SARS-CoV-2 in rural counties compared to urban ones throughout the study period. CONCLUSION State and county policies had an impact on local pandemic trajectories. The rural-urban disparities in case burden call for evidence-based approaches in tailoring health promotion interventions and vaccination campaigns to rural residents.
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Yuan P, Aruffo E, Gatov E, Tan Y, Li Q, Ogden N, Collier S, Nasri B, Moyles I, Zhu H. School and community reopening during the COVID-19 pandemic: a mathematical modelling study. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211883. [PMID: 35127115 PMCID: PMC8808096 DOI: 10.1098/rsos.211883] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/04/2022] [Indexed: 05/03/2023]
Abstract
Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. Using demographic and epidemiological data between 31 July and 23 November 2020 from Toronto, Canada, we developed a compartmental transmission model with age, household and setting structure to study the impact of schools reopening in September 2020. The model simulates transmission in the home, community and schools, accounting for differences in infectiousness between adults and children, and accounting for work-from-home and virtual learning. While we found a slight increase in infections among adults (2.2%) and children (4.5%) within the first eight weeks of school reopening, transmission in schools was not the key driver of the virus resurgence in autumn 2020. Rather, it was community spread that determined the outbreak trajectory, primarily due to increases in contact rates among adults in the community after school reopening. Analyses of cross-infection among households, communities and schools revealed that home transmission is crucial for epidemic progression and safely operating schools, while the degree of in-person attendance has a larger impact than other control measures in schools. This study suggests that safe school reopening requires the strict maintenance of public health measures in the community.
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Affiliation(s)
- Pei Yuan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, Canada
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Department of Mathematics and Statistics, York University, Toronto, Canada
| | - Elena Aruffo
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, Canada
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Department of Mathematics and Statistics, York University, Toronto, Canada
| | - Evgenia Gatov
- Toronto Public Health, City of Toronto, Toronto, Ontario, Canada
| | - Yi Tan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, Canada
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Department of Mathematics and Statistics, York University, Toronto, Canada
| | - Qi Li
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, Canada
- Department of Mathematics, Shanghai Normal University, Shanghai, People's Republic of China
| | - Nick Ogden
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Quebec, Canada
| | - Sarah Collier
- Toronto Public Health, City of Toronto, Toronto, Ontario, Canada
| | - Bouchra Nasri
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Department of Social and Preventive Medicine, Université de Montréal, Montréal, Quebec, Canada
| | - Iain Moyles
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Department of Mathematics and Statistics, York University, Toronto, Canada
| | - Huaiping Zhu
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, Canada
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
- Department of Mathematics and Statistics, York University, Toronto, Canada
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POZZOBON ALLANPB, PETRY ANAC, ZILBERBERG CARLA, BARROS CINTIAMDE, NEPOMUCENO-SILVA JOSÉL, FEITOSA NATÁLIAM, GOMES NETO LUPISR, RODRIGUES BRUNOC, BRINDEIRO RODRIGOM, NOCCHI KEITYJAQUELINEC, MURY FLAVIAB, SOUZA-MENEZES JACKSONDE, SILVA MANUELALDA, MEDEIROS MARCIOJOSÉDE, GESTINARI RAQUELS, ALVARENGA ALESSANDRASDE, SILVA CARINAA, SANTOS DANIELEGDOS, SILVESTRE DIEGOHENRIQUE, SOUSA GRAZIELEFDE, ALMEIDA JANIMAYRIFDE, SILVA JHENIFERNDA, BRANDÃO LAYZAM, DRUMMOND LEANDROO, CARPES RAPHAELM, SANTOS RENATACDOS, PORTAL TAYNANM, TANURI AMILCAR, NUNES-DA-FONSECA RODRIGO. Schools reopening and the COVID-19 pandemic: a case study from Macaé, Rio de Janeiro, Brazil. AN ACAD BRAS CIENC 2022; 94:e20211361. [DOI: 10.1590/0001-3765202220211361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 01/16/2022] [Indexed: 12/23/2022] Open
Affiliation(s)
| | - ANA C. PETRY
- Universidade Federal do Rio de Janeiro (UFRJ), Brazil
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