论文标题
干预对COVID-19在印度传播的影响：基于模型的研究
Impact of intervention on the spread of COVID-19 in India: A model based study
论文作者
论文摘要
病毒严重急性呼吸综合症2（SARS-COV-2）引起的Corona病毒疾病（COVID-19）的爆发已经在世界上几乎每个国家都造成了紧急情况。该疾病于2019年12月在中国武汉首次识别后，在很短的时间内蔓延到世界各地。在印度，疫情以$ 2^{nd} $ 2020的爆发开始，此后案件呈指数增长。人口密度很高，特定药物或疫苗的无法获得，关于疾病传播机制的证据不足也使得在印度适当地与疾病作斗争变得困难。数学模型已用于预测疾病动态，并评估减轻疾病负担的干预策略的效率。在这项工作中，我们提出了一个数学模型来描述个体之间的疾病传播机制。 We consider the initial phase of the outbreak situation in India and our proposed model is fitted to the daily cumulative new reported cases during the period $2^{nd}$ March, 2020 to $24^{th}$ March, 2020. We estimate the basic reproduction number $(R_0)$, effective reproduction number (R(t)) and epidemic doubling time from the incidence data for the above-mentioned period.我们进一步评估了预防措施的影响，例如在减少新案件中的意识，锁定，适当的手消毒等方面的传播。根据实施期间干预强度的可变性，考虑了两种干预方案。我们的研究表明，在印度较短的时间内控制疾病爆发需要更高的干预工作。此外，我们的分析表明，应在有效地消除疾病的时间内加强干预措施的强度。
The outbreak of corona virus disease 2019 (COVID-19), caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already created emergency situations in almost every country of the world. The disease spreads all over the world within a very short period of time after its first identification in Wuhan, China in December, 2019. In India, the outbreaks starts on $2^{nd}$ March, 2020 and after that the cases are increasing exponentially. Very high population density, the unavailability of specific medicines or vaccines, insufficient evidences regarding the transmission mechanism of the disease also make it difficult to fight against the disease properly in India. Mathematical models have been used to predict the disease dynamics and also to assess the efficiency of the intervention strategies in reducing the disease burden. In this work, we propose a mathematical model to describe the disease transmission mechanism between the individuals. We consider the initial phase of the outbreak situation in India and our proposed model is fitted to the daily cumulative new reported cases during the period $2^{nd}$ March, 2020 to $24^{th}$ March, 2020. We estimate the basic reproduction number $(R_0)$, effective reproduction number (R(t)) and epidemic doubling time from the incidence data for the above-mentioned period. We further assess the effect of preventive measures such as spread of awareness, lock-down, proper hand sanitization, etc. in reducing the new cases. Two intervention scenarios are considered depending on the variability of the intervention strength over the period of implementation. Our study suggests that higher intervention effort is required to control the disease outbreak within a shorter period of time in India. Moreover, our analysis reveals that the strength of the intervention should be strengthened over the time to eradicate the disease effectively.
