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1.
Sci Rep ; 11(1): 20451, 2021 10 14.
Article in English | MEDLINE | ID: covidwho-1469991

ABSTRACT

This research measures the epidemiological and economic impact of COVID-19 spread in the US under different mitigation scenarios, comprising of non-pharmaceutical interventions. A detailed disease model of COVID-19 is combined with a model of the US economy to estimate the direct impact of labor supply shock to each sector arising from morbidity, mortality, and lockdown, as well as the indirect impact caused by the interdependencies between sectors. During a lockdown, estimates of jobs that are workable from home in each sector are used to modify the shock to labor supply. Results show trade-offs between economic losses, and lives saved and infections averted are non-linear in compliance to social distancing and the duration of the lockdown. Sectors that are worst hit are not the labor-intensive sectors such as the Agriculture sector and the Construction sector, but the ones with high valued jobs such as the Professional Services, even after the teleworkability of jobs is accounted for. Additionally, the findings show that a low compliance to interventions can be overcome by a longer shutdown period and vice versa to arrive at similar epidemiological impact but their net effect on economic loss depends on the interplay between the marginal gains from averting infections and deaths, versus the marginal loss from having healthy workers stay at home during the shutdown.


Subject(s)
COVID-19/epidemiology , Agriculture/economics , COVID-19/economics , COVID-19/prevention & control , Communicable Disease Control , Construction Industry/economics , Employment , Humans , Industry/economics , Models, Economic , SARS-CoV-2/isolation & purification , Teleworking , United States/epidemiology
2.
medRxiv ; 2020 Nov 30.
Article in English | MEDLINE | ID: covidwho-955699

ABSTRACT

This research measures the epidemiological and economic impact of COVID-19 spread in the US under different mitigation scenarios, comprising of non-pharmaceutical interventions. A detailed disease model of COVID-19 is combined with a model of the US economy to estimate the direct impact of labor supply shock to each sector arising from morbidity, mortality, and lock down, as well as the indirect impact caused by the interdependencies between sectors. During a lockdown, estimates of jobs that are workable from home in each sector are used to modify the shock to labor supply. Results show trade-offs between economic losses, and lives saved and infections averted are non-linear in compliance to social distancing and the duration of lockdown. Sectors that are worst hit are not the labor-intensive sectors such as Agriculture and Construction, but the ones with high valued jobs such as Professional Services, even after the teleworkability of jobs is accounted for. Additionally, the findings show that a low compliance to interventions can be overcome by a longer shutdown period and vice versa to arrive at similar epidemiological impact but their net effect on economic loss depends on the interplay between the marginal gains from averting infections and deaths, versus the marginal loss from having healthy workers stay at home during the shutdown.

3.
Sci Rep ; 10(1): 18422, 2020 10 28.
Article in English | MEDLINE | ID: covidwho-894412

ABSTRACT

We use an individual based model and national level epidemic simulations to estimate the medical costs of keeping the US economy open during COVID-19 pandemic under different counterfactual scenarios. We model an unmitigated scenario and 12 mitigation scenarios which differ in compliance behavior to social distancing strategies and in the duration of the stay-home order. Under each scenario we estimate the number of people who are likely to get infected and require medical attention, hospitalization, and ventilators. Given the per capita medical cost for each of these health states, we compute the total medical costs for each scenario and show the tradeoffs between deaths, costs, infections, compliance and the duration of stay-home order. We also consider the hospital bed capacity of each Hospital Referral Region (HRR) in the US to estimate the deficit in beds each HRR will likely encounter given the demand for hospital beds. We consider a case where HRRs share hospital beds among the neighboring HRRs during a surge in demand beyond the available beds and the impact it has in controlling additional deaths.


Subject(s)
Coronavirus Infections/economics , Health Care Costs/statistics & numerical data , Pandemics/economics , Pneumonia, Viral/economics , COVID-19 , Capacity Building/economics , Capacity Building/statistics & numerical data , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Health Facilities/economics , Health Facilities/statistics & numerical data , Humans , Infection Control/economics , Infection Control/statistics & numerical data , Models, Statistical , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , United States
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