Healthcare impact of COVID-19 epidemic in Nigeria: A stochastic mathematical model
WHO declared COVID-19 a pandemic on 11 March 2020.1 Worldwide it has exploded to 784,794 cases and caused 37,788 deaths by 30 Mar 2020.2 In India the first case was reported on 30 Jan. By 30 Mar, India had reported 1,251 cases and 32 deaths.3 The spread of any epidemic depends on infectivity of the pathogen and the available susceptible population. For a novel infection, when disease dynamics are still unclear, mathematical modeling estimates the number of cases in worst and best-case scenarios. It can also help estimate the effect of preventive measures adopted against COVID-19.
With Suppressive strategies, the aim is to maintain the effective Reproduction number (R) below 01, to prevent further spread of infection, while in a Mitigation strategy, the aim is to blunt the effect of the epidemic.4 Non-Pharmacological interventions (NPIs) utilized to contain epidemics (Social distancing, closure of schools, universities and offices, avoidance of mass gatherings, community-wide containment etc.) may be applied to the general population, contacts of cases (Contact tracing, Surveillance, quarantine) and the cases themselves (Early Reporting, Isolation).4,5 India appears to be in early stages of the epidemic. It is important to predict how the disease is likely to evolve amongst the population. This will help in estimation of health care requirements and permit a measured allocation of resources.
Considering the differences in the way COVID-19 has spread in different countries, any planning for mounting a fresh response has to be adaptable and situation-specific. When the actual numbers are relatively few, a mathematical simulation approach is best suited towards understanding this epidemic and formulating an appropriate response.
Hence, we decided to create a early stochastic mathematical model of the COVID-19 epidemic in India with the objective of determining it’s magnitude, assessing the impact on health care resources and studying the effect of certain NPIs on the epidemic.