MITIGATING THE 4th WAVE OF THE COVID-19 PANDEMIC IN ONTARIO
Cipriano, L. E.; Haddara, W. M. R.; Sander, B.
10.1101/2021.09.02.21263000 medRxivShow abstract
BackgroundThe goal of this study was to project the number of COVID-19 cases and demand for acute hospital resources for Fall of 2021 in a representative mid-sized community in southwestern Ontario. We sought to evaluate whether current levels of vaccine coverage and contact reduction could mitigate a potential 4th wave fueled by the Delta variant, or whether the reinstitution of more intense public health measures will be required. MethodsWe developed an age-stratified dynamic transmission model of COVID-19 in a mid-sized city (population 500,000) currently experiencing a relatively low, but increasing, infection rate in Step 3 of Ontarios Wave 3 recovery. We parameterized the model using the medical literature, grey literature, and government reports. We estimated the current level of contact reduction by model calibration to cases and hospitalizations. We projected the number of infections, number of hospitalizations, and the time to re-instate high intensity public health measures over the fall of 2021 under different levels of vaccine coverage and contact reduction. ResultsMaintaining contact reductions at the current level, estimated to be a 17% reduction compared to pre-pandemic contact levels, results in COVID-related admissions exceeding 20% of pre-pandemic critical care capacity by late October, leading to cancellation of elective surgeries and other non-COVID health services. At high levels of vaccination and relatively high levels of mask wearing, a moderate additional effort to reduce contacts (30% reduction compared to pre-pandemic contact levels), is necessary to avoid re-instating intensive public health measures. Compared to prior waves, the age distribution of both cases and hospitalizations shifts younger and the estimated number of pediatric critical care hospitalizations may substantially exceed 20% of capacity. DiscussionHigh rates of vaccination coverage in people over the age of 12 and mask wearing in public settings will not be sufficient to prevent an overwhelming resurgence of COVID-19 in the Fall of 2021. Our analysis indicates that immediate moderate public health measures can prevent the necessity for more intense and disruptive measures later.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Estimating COVID-19 cases and deaths prevented by non-pharmaceutical interventions in 2020-2021, and the impact of individual actions: a retrospective model-based analysis 97%
- Estimating measures to reduce the transmission of SARS-CoV-2 in Australia to guide a ‘National Plan’ to reopening 95%
- Estimating the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission in Australia 95%
Similar papers in this journal
- Testing and Vaccination to Reduce the Impact of COVID-19 in Nursing Homes: An Agent-Based Approach 95%
- Modelling testing and response strategies for COVID-19 outbreaks in remote Australian Aboriginal communities 95%
- Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases 95%
Similar papers in this journal
- Interventions to control nosocomial transmission of SARS-CoV-2: a modelling study 96%
- Non-pharmaceutical interventions and vaccinating school children required to contain SARS-CoV-2 Delta variant outbreaks in Australia: a modelling analysis 95%
- SARS-CoV-2 infection risk during delivery of childhood vaccination campaigns: a modelling study 95%
Similar papers in this journal
Similar papers in this journal
- The impact of vaccination on COVID-19 outbreaks in the United States 96%
- Mathematical modeling to inform vaccination strategies and testing approaches for COVID-19 in nursing homes 95%
- Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.