Abstract
The state of Kuwait is facing a substantial challenge in responding to the spread of the novel coronavirus 2019 (COVID-19). The government’s decision to repatriate stranded citizens back to Kuwait from various COVID-19 epicenters has generated a great concern. It has heightened the need for prediction models to estimate the epidemic size. Mathematical modeling plays a pivotal role in predicting the spread of infectious diseases to enable policymakers to implement various health and safety measures to contain the spread. This research presents a forecast of the COVID-19 epidemic size in Kuwait based on the confirmed data. Deterministic and stochastic modeling approaches were used to estimate the size of COVID-19 spread in Kuwait and determine its ending phase. In addition, various simulation scenarios were conducted to demonstrate the effectiveness of nonpharmaceutical intervention measures, particularly with time-varying infection rates and individual contact numbers. Results indicate that, with data until 19 April 2020 and before the repatriation plan, the estimated reproduction number in Kuwait is 2.2. It also confirms the efficiency of the containment measures of the state of Kuwait to control the spread even after the repatriation plan. The results show that a high contact rate among the population implies that the epidemic peak value is yet to be reached and that more strict intervention measures must be incorporated
Highlights
Since the detection of the first case of the novel coronavirus 2019 (COVID-19) in December 2019 in Wuhan City, Hubei Province, China, the number of identified cases has been increasing rapidly.Significant spread prevention measures were implemented by the Chinese government such as locking down the city of Wuhan and closing routes to all cities in Hubei Province in late January 2020
The results showed that reducing the number of contacts and complying with the social distancing regulations would significantly reduce the epidemic peak value
A forecast of COVID-19 spread in Kuwait was carried out using various deterministic and stochastic modeling approaches
Summary
Since the detection of the first case of the novel coronavirus 2019 (COVID-19) in December 2019 in Wuhan City, Hubei Province, China, the number of identified cases has been increasing rapidly. Significant spread prevention measures were implemented by the Chinese government such as locking down the city of Wuhan and closing routes to all cities in Hubei Province in late January 2020. Despite these measures, the COVID-19 disease spread globally and was declared as an epidemic by the World. The drastic increase in the number of cases for COVID-19 became an emergency and a profound health issue worldwide. The COVID-19 characteristics of strong infectivity, long incubation period, difficulties of detection, and uncertainty in ways of transmission increase the vagueness and the complications of controlling the outbreak
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