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Optimal shutdown strategies for COVID-19 with economic and mortality costs: British Columbia as a case study.

ABSTRACT: Decision makers with the responsibility of managing policy for the COVID-19 epidemic have faced difficult choices in balancing the competing claims of saving lives and the high economic cost of shutdowns. In this paper, we formulate a model with both epidemiological and economic content to assist this decision-making process. We consider two ways to handle the balance between economic costs and deaths. First, we use the statistical value of life, which in Canada is about C$7 million, to optimize over a single variable, which is the sum of the economic cost and the value of lives lost. Our second method is to calculate the Pareto optimal front when we look at the two variables-deaths and economic costs. In both cases we find that, for most parameter values, the optimal policy is to adopt an initial shutdown level which reduces the reproduction number of the epidemic to close to 1. This level is then reduced once a vaccination programme is underway. Our model also indicates that an oscillating policy of strict and mild shutdowns is less effective than a policy which maintains a moderate shutdown level.

SUBMITTER: Barlow MT

PROVIDER: S-EPMC8424295 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Optimal shutdown strategies for COVID-19 with economic and mortality costs: British Columbia as a case study.

Barlow M T MT Marshall N D ND Tyson R C RC

Royal Society open science 20210908 9

Decision makers with the responsibility of managing policy for the COVID-19 epidemic have faced difficult choices in balancing the competing claims of saving lives and the high economic cost of shutdowns. In this paper, we formulate a model with both epidemiological and economic content to assist this decision-making process. We consider two ways to handle the balance between economic costs and deaths. First, we use the statistical value of life, which in Canada is about C$7 million, to optimize ...[more]

PMID: 34527265

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Project description:BackgroundCOVID-19 imposed substantial health and economic burdens. Comprehensive population-based estimates of health care costs for COVID-19 are essential for planning and policy evaluation. We estimated publicly funded health care costs in 2 Canadian provinces during the pandemic's first wave.MethodsIn this historical cohort study, we linked patients with their first positive SARS-CoV-2 test result by June 30, 2020, in 2 Canadian provinces (British Columbia and Ontario) to health care administrative databases and matched to negative or untested controls. We stratified patients by highest level of initial care: community, long-term care, hospital (without admission to the intensive care unit [ICU]) and ICU. Mean publicly funded health care costs for patients and controls, mean net (attributable to COVID-19) costs and total costs were estimated from 30 days before to 120 days after the index date, or to July 31, 2020, in 30-day periods for patients still being followed by the start of each period.ResultsWe identified 2465 matched people with a positive test result for SARS-CoV-2 in BC and 28 893 in Ontario. Mean age was 53.4 (standard deviation [SD] 21.8) years (BC) and 53.7 (SD 22.7) years (Ontario); 55.7% (BC) and 56.1% (Ontario) were female. Net costs in the first 30 days after the index date were $22 010 (95% confidence interval [CI] 19 512 to 24 509) and $15 750 (95% CI 15 354 to 16 147) for patients admitted to hospital, and $65 828 (95% CI 58 535 to 73 122) and $56 088 (95% CI 53 721 to 58 455) for ICU patients in BC and Ontario, respectively. In the community and long-term care settings, net costs were near 0. Total costs for all people, from 30 days before to 30 days after the index date, were $22 128 330 (BC) and $175 778 210 (Ontario).InterpretationDuring the first wave, we found that mean costs attributable to COVID-19 were highest for patients with ICU admission and higher in BC than Ontario. Reducing the number of people who acquire COVID-19 and severity of illness are required to mitigate the economic impact of COVID-19.

Project description:OBJECTIVES:A current diagnosis of asthma cannot be objectively confirmed in many patients with physician-diagnosed asthma. Estimates of resource use in overdiagnosed cases of asthma are necessary to measure the burden of overdiagnosis and to evaluate strategies to reduce this burden. We assessed differences in asthma-related healthcare resource use between patients with a confirmed asthma diagnosis and those with asthma ruled out. DESIGN:Population-based, prospective cohort study. SETTING:Participants were recruited through random-digit dialling of both landlines and mobile phones in the province of British Columbia, Canada. PARTICIPANTS:We included 345 individuals ≥12 years of age with a self-reported physician diagnosis of asthma. The diagnosis of asthma was reassessed at the end of 12 months of follow-up using a structured algorithm, which included a bronchodilator reversibility test, methacholine challenge test, and if necessary medication tapering and a second methacholine challenge test. PRIMARY AND SECONDARY OUTCOME MEASURES:Self-reported annual asthma-related direct healthcare costs (2017 Canadian dollars), outpatient physician visits and medication use from the perspective of the Canadian healthcare system. RESULTS:Asthma was ruled out in 86 (24.9%) participants. The average annual asthma-related direct healthcare costs for participants with confirmed asthma were $C497.9 (SD $C677.9) and for participants with asthma ruled out, $C307.7 (SD $C424.1). In the adjusted analyses, a confirmed diagnosis was associated with higher direct healthcare costs (relative ratio (RR)=1.60, 95% CI 1.14 to 2.22), increased rate of specialist visits (RR=2.41, 95% CI 1.05 to 5.40) and reliever medication use (RR=1.62, 95% CI 1.09 to 2.35), but not primary care physician visits (p=0.10) or controller medication use (p=0.11). CONCLUSIONS:A quarter of individuals with a physician diagnosis of asthma did not have asthma after objective re-evaluation. These participants still consumed a significant amount of asthma-related healthcare resources. The population-level economic burden of asthma overdiagnosis could be substantial.

Project description:BackgroundClose-contact rates are thought to be a driving force behind the transmission of many infectious respiratory diseases. Yet, contact rates and their relation to transmission and the impact of control measures, are seldom quantified. We quantify the response of contact rates, reported cases and transmission of COVID-19, to public health contact-restriction orders, and examine the associations among these three variables in the province of British Columbia, Canada.MethodsWe derived time series data for contact rates, daily cases and transmission of COVID-19 from a social contacts survey, reported case counts and by fitting a transmission model to reported cases, respectively. We used segmented regression to investigate impacts of public health orders; Pearson correlation to determine associations between contact rates and transmission; and vector autoregressive modeling to quantify lagged associations between contacts rates, daily cases, and transmission.ResultsDeclines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in cases showed a reporting delay of about 2 weeks. Contact rates were a significant driver of COVID-19 and explained roughly 19 and 20% of the variation in new cases and transmission, respectively. Interestingly, increases in COVID-19 transmission and cases were followed by reduced contact rates: overall, daily cases explained about 10% of the variation in subsequent contact rates.ConclusionWe showed that close-contact rates were a significant time-series driver of transmission and ultimately of reported cases of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest possible behavioral feedback, by which increased reported cases lead to reduced subsequent contact rates. Our findings help to explain and validate the commonly assumed, but rarely measured, response of close contact rates to public health guidelines and their impact on the dynamics of infectious diseases.

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Optimal shutdown strategies for COVID-19 with economic and mortality costs: British Columbia as a case study.

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Optimal shutdown strategies for COVID-19 with economic and mortality costs: British Columbia as a case study.

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