Early Detection of COVID-19 Waves From Cases in a Neighboring Country With an Open Border

Border closure or travel restriction is a critical issue as closing the border early can badly affect the economy of the country, whereas substantial delay can put human lives at stake. While many papers discuss closing the border early in the pandemic, the question of when to close the border has not been addressed well. We have tried to estimate a date of closing the border by taking the reference of a neighboring country with a high correlation in Covid-19 incidence. Here we have used non-linear methods to probe the landscape of correlation between temporal COVID-19 incidences and deaths. We have tested our method on two neighboring countries, Nepal and India, with open borders, where closing the borders are among the top priorities to reduce the spread and spill-out of variants. We have selected these countries as they have close connectivity and intertwined socio-economic network with thousands of people crossing the border every day. We found the distance correlation for COVID-19 incidence between these countries to be statistically significant (p < 0.001) and there is a lag of 6 days for maximum correlation. In addition, we analyzed the correlation for each wave and found the distance correlation for the first phase is 0.8145 (p < 0.001) with a lag of 2 days, and the distance correlation for the second wave is 0.9685 (p < 0.001) without any lag. This study can be a critical planning tool for policymakers and public health practitioners to make an informed decision on border closure in the early days as it is critically associated with the legal and diplomatic agreements and regulations between two countries.

Automated summary

This study investigated the correlation between COVID-19 incidence and deaths in neighboring countries, estimating the timing for border closure based on a high correlation reference. Significant distance correlation between Nepal and India was found, providing critical insights for policymakers and public health practitioners to make informed decisions on early border closure.