Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data

Bhatia, Rajiv; Klausner, Jeffrey D.

doi:10.1371/journal.pone.0243026

Cited by 14 publications

(11 citation statements)

References 27 publications

(34 reference statements)

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“…The virus is transmitted to susceptible individuals if they are in close contact with the infectious host with probability ϵ . For COVID-19 the probability of infection per exposure is around 0.1 [ 72 , 73 ], and comparatively, the new COVID variant is estimated to be approximately 56% more transmissible (95% credible interval 50–74%) [ 74 ], and therefore we consider both cases with transmission probabilities set to ϵ = 0.1, 0.156.…”

Section: Simulationsmentioning

confidence: 99%

Mechanistic modelling of COVID-19 and the impact of lockdowns on a short-time scale

et al. 2021

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Background To mitigate the spread of the COVID-19 coronavirus, some countries have adopted more stringent non-pharmaceutical interventions in contrast to those widely used. In addition to standard practices such as enforcing curfews, social distancing, and closure of non-essential service industries, other non-conventional policies also have been implemented, such as the total lockdown of fragmented regions, which are composed of sparsely and highly populated areas. Methods In this paper, we model the movement of a host population using a mechanistic approach based on random walks, which are either diffusive or super-diffusive. Infections are realised through a contact process, whereby a susceptible host is infected if in close spatial proximity of the infectious host with an assigned transmission probability. Our focus is on a short-time scale (∼ 3 days), which is the average time lag time before an infected individual becomes infectious. Results We find that the level of infection remains approximately constant with an increase in population diffusion, and also in the case of faster population dispersal (super-diffusion). Moreover, we demonstrate how the efficacy of imposing a lockdown depends heavily on how susceptible and infectious individuals are distributed over space. Conclusion Our results indicate that on a short-time scale, the type of movement behaviour does not play an important role in rising infection levels. Also, lock-down restrictions are ineffective if the population distribution is homogeneous. However, in the case of a heterogeneous population, lockdowns are effective if a large proportion of infectious carriers are distributed in sparsely populated sub-regions.

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Section: Simulationsmentioning

confidence: 99%

Mechanistic modelling of COVID-19 and the impact of lockdowns on a short-time scale

et al. 2021

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“…Our simulation began on February 29, 2020, and terminated on March 14, 2020. The main realistic parameters were p I =1/40,500 (extracted from Bhatia and Klausner [ 27 ]) and p D =0.3 (estimated from Worldometer [ 28 ], which has also been cited by Dhillon et al [ 29 ]).…”

Section: Resultsmentioning

confidence: 95%

A Full-Scale Agent-Based Model to Hypothetically Explore the Impact of Lockdown, Social Distancing, and Vaccination During the COVID-19 Pandemic in Lombardy, Italy: Model Development

Giacopelli¹

2021

JMIRx Med

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Background The COVID-19 outbreak, an event of global concern, has provided scientists the opportunity to use mathematical modeling to run simulations and test theories about the pandemic. Objective The aim of this study was to propose a full-scale individual-based model of the COVID-19 outbreak in Lombardy, Italy, to test various scenarios pertaining to the pandemic and achieve novel performance metrics. Methods The model was designed to simulate all 10 million inhabitants of Lombardy person by person via a simple agent-based approach using a commercial computer. In order to obtain performance data, a collision detection model was developed to enable cluster nodes in small cells that can be processed fully in parallel. Within this collision detection model, an epidemic model based mostly on experimental findings about COVID-19 was developed. Results The model was used to explain the behavior of the COVID-19 outbreak in Lombardy. Different parameters were used to simulate various scenarios relating to social distancing and lockdown. According to the model, these simple actions were enough to control the virus. The model also explained the decline in cases in the spring and simulated a hypothetical vaccination scenario, confirming, for example, the herd immunity threshold computed in previous works. Conclusions The model made it possible to test the impact of people’s daily actions (eg, maintaining social distance) on the epidemic and to investigate interactions among agents within a social network. It also provided insight on the impact of a hypothetical vaccine.

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“…at work); or environmental (there has been no direct contact between the index and secondary case, and transmission is via a contaminated surface or airborne particles). These are weighted by the relative attack rates for each contact route, w route , based on the observation that within-household transmission accounts for two to three times more infections than outside-household transmission [19,20], and the assumption of [14] that around 10% of all transmission is environmental. The model has no fixed household size as we are only interested in the very early stages before the outbreak is detected, where only one or two household members are typically infected.…”

Section: Scenario 2: Community Outbreak Seeded By a Frontline Workermentioning

confidence: 99%

Managing the risk of a COVID-19 outbreak from border arrivals

Steyn

Plank

James

et al. 2021

J. R. Soc. Interface.

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In an attempt to maintain the elimination of COVID-19 in New Zealand, all international arrivals are required to spend 14 days in government-managed quarantine and to return a negative test result before being released. We model the testing, isolation and transmission of COVID-19 within quarantine facilities to estimate the risk of community outbreaks being seeded at the border. We use a simple branching process model for COVID-19 transmission that includes a time-dependent probability of a false-negative test result. We show that the combination of 14-day quarantine with two tests is highly effective in preventing an infectious case entering the community, provided there is no transmission within quarantine facilities. Shorter quarantine periods, or reliance on testing only with no quarantine, substantially increases the risk of an infectious case being released. We calculate the fraction of cases detected in the second week of their two-week stay and show that this may be a useful indicator of the likelihood of transmission occurring within quarantine facilities. Frontline staff working at the border risk exposure to infected individuals and this has the potential to lead to a community outbreak. We use the model to test surveillance strategies and evaluate the likely size of the outbreak at the time it is first detected. We conclude with some recommendations for managing the risk of potential future outbreaks originating from the border.

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Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data

Cited by 14 publications

References 27 publications

Mechanistic modelling of COVID-19 and the impact of lockdowns on a short-time scale

Mechanistic modelling of COVID-19 and the impact of lockdowns on a short-time scale

A Full-Scale Agent-Based Model to Hypothetically Explore the Impact of Lockdown, Social Distancing, and Vaccination During the COVID-19 Pandemic in Lombardy, Italy: Model Development

Managing the risk of a COVID-19 outbreak from border arrivals

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