Yaladanda Nikhila, Mopuri Rajasekhar, Vavilala Hari Prasad, Mutheneni Srinivasa Rao
ENVIS Resource Partner on Climate Change and Public Health, Applied Biology Division, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Tarnaka, Hyderabad, 500007, Telangana, India.
Clin Epidemiol Glob Health. 2022 May-Jun;15:101052. doi: 10.1016/j.cegh.2022.101052. Epub 2022 May 5.
The outbreak of Coronavirus disease (COVID-19) has swiftly spread globally and caused public health and socio-economic disruption in many countries. An epidemiological modelling studies in the susceptible-infectious-removed (SIR) has played an important role for making effective public health policy to mitigate the spread of COVID-19. The aim of the present study is to investigate the optimal vaccination strategy to control the COVID-19 pandemic in India.
We have applied compartment mathematical model susceptible-vaccination-infectious-removed (SVIR) with different range of vaccine efficacy scenarios and predicted the population to be covered for vaccination per day in India as well as state level was performed.
The model assumed that a vaccine has 100% efficacy, predicted that >5 million populace to be vaccinated per day to flatten the epidemic curve in India. Similarly, different vaccination mechanisms such as 'all-or-nothing' (AoN) and leaky vaccines does not have potential discordance in their effectiveness at higher efficacies (>70%). However, AoN vaccine was found to be marginally effective than leaky at lower efficacies (<70%) when administered at the higher coverage strategies. Further state level analyses were performed and it was found that 0.3, 0.3, 0.2 and 1 million vaccinations required per day in Andhra Pradesh, Gujarat, Kerala and Maharashtra as it assumes that the vaccine efficacy is 70%.
The proposed modelling approach shows a range of assumptions on the efficacy of vaccine which helps the health authorities to prioritize the vaccination strategies to prevent the transmission as well as disease.
冠状病毒病(COVID-19)疫情已在全球迅速蔓延,给许多国家的公共卫生和社会经济带来了破坏。基于易感-感染-康复(SIR)模型的流行病学建模研究在制定有效的公共卫生政策以减轻COVID-19传播方面发挥了重要作用。本研究的目的是调查在印度控制COVID-19大流行的最佳疫苗接种策略。
我们应用了具有不同疫苗效力情景范围的分区数学模型易感-接种-感染-康复(SVIR),并预测了印度每天需要接种疫苗的人群数量,同时也在邦一级进行了预测。
该模型假设疫苗效力为100%,预测在印度每天需要超过500万人接种疫苗才能使疫情曲线趋于平缓。同样,不同的疫苗接种机制,如“全有或全无”(AoN)和有漏洞的疫苗,在效力较高(>70%)时其有效性没有潜在差异。然而,在高覆盖率策略下,当效力较低(<70%)时,发现AoN疫苗的有效性略高于有漏洞的疫苗。进一步进行了邦一级的分析,发现在假设疫苗效力为70%的情况下,安得拉邦、古吉拉特邦、喀拉拉邦和马哈拉施特拉邦每天分别需要0.3、0.3、0.2和100万次疫苗接种。
所提出的建模方法展示了一系列关于疫苗效力的假设,这有助于卫生当局确定疫苗接种策略的优先级,以预防传播和疾病。