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1. A versatile web app for identifying the drivers of COVID-19 epidemics

   https://doi.org/10.1186/s12967-021-02736-2  

   Getz, Wayne M.; Salter, Richard; Luisa Vissat, Ludovica; Horvitz, Nir (March 2021, Journal of Translational Medicine)

   Abstract BackgroundNo versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. Thehttp://covid-webapp.numerusinc.com/web app presented here fills this gap. MethodsOur web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. ResultsWe illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world’s fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. ConclusionOur web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration. 

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2. COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

   https://doi.org/10.1177/0272989X211003081  

   Lee, Serin; Zabinsky, Zelda_B; Wasserheit, Judith_N; Kofsky, Stephen_M; Liu, Shan (March 2021, Medical Decision Making)

   As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021. 

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3. The implications of silent transmission for the control of COVID-19 outbreaks

   https://doi.org/10.1073/pnas.2008373117  

   Moghadas, Seyed M.; Fitzpatrick, Meagan C.; Sah, Pratha; Pandey, Abhishek; Shoukat, Affan; Singer, Burton H.; Galvani, Alison P. (July 2020, Proceedings of the National Academy of Sciences)

   null (Ed.)

   Since the emergence of coronavirus disease 2019 (COVID-19), unprecedented movement restrictions and social distancing measures have been implemented worldwide. The socioeconomic repercussions have fueled calls to lift these measures. In the absence of population-wide restrictions, isolation of infected individuals is key to curtailing transmission. However, the effectiveness of symptom-based isolation in preventing a resurgence depends on the extent of presymptomatic and asymptomatic transmission. We evaluate the contribution of presymptomatic and asymptomatic transmission based on recent individual-level data regarding infectiousness prior to symptom onset and the asymptomatic proportion among all infections. We found that the majority of incidences may be attributable to silent transmission from a combination of the presymptomatic stage and asymptomatic infections. Consequently, even if all symptomatic cases are isolated, a vast outbreak may nonetheless unfold. We further quantified the effect of isolating silent infections in addition to symptomatic cases, finding that over one-third of silent infections must be isolated to suppress a future outbreak below 1% of the population. Our results indicate that symptom-based isolation must be supplemented by rapid contact tracing and testing that identifies asymptomatic and presymptomatic cases, in order to safely lift current restrictions and minimize the risk of resurgence. 

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4. Data-driven optimized control of the COVID-19 epidemics

   https://doi.org/10.1038/s41598-021-85496-9  

   Shirin, Afroza; Lin, Yen Ting; Sorrentino, Francesco (December 2021, Scientific Reports)

   null (Ed.)

   Abstract Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening ‘in phases’. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population. 

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5. Harnessing testing strategies and public health measures to avert COVID-19 outbreaks during ocean cruises

   https://doi.org/doi.org/10.1038/s41598-021-95032-4  

   Chowell, G. (January 2021, Scientific reports)

   To ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the test’s sensitivity profile, and testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures. 

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