Analytical Model of COVID 19 for lifting non pharmaceutical interventions

In the present work, we outline a set of coarse-grain analytical models that can be used by decision-makers to bound the potential impact of the COVID-19 pandemic on specific communities with known or estimated social contact structure and to assess the effects of various non-pharmaceutical interventions on slowing the progression of disease spread. This work provides a multi-dimensional view of the problem by examining steady-state and dynamic disease spread using a network-based approach. In addition, Bayesian-based estimation procedures are used to provide a realistic assessment of the severity of outbreaks based on estimates of the average and instantaneous basic reproduction number R . ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement No external funding was received. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: N/A All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The validation data is publicly available and cited in the paper.