Geospatial analysis of contagious infection growth and cross-boundary transmission in non-vaccinated districts of North-East Indian states during the COVID-19 pandemic

Background

During the initial phase of the COVID-19 pandemic, the Government of India implemented a nationwide lockdown, sealing borders across states and districts. The northeastern region of India, surrounded by three international borders and connected to mainland India by a narrow passage, faced particular isolation. This isolation resulted in these states forming a relatively closed population. Consequently, the availability of population-based data from Indian Council of Medical Research, tracked through national identification cards, offered a distinctive opportunity to understand the spread of the virus among non-vaccinated and non-exposed populations. This research leverages this dataset to comprehend the repercussions within isolated populations.

Methods

The inter-district variability was visualized using geospatial analysis. The patterns do not follow any established grounded theories on disease spread. Out of 7.1 million total data weekly 0.35 million COVID-19-positive northeast data was taken from April 2020 to February 2021 including “date, test result, population density, area, latitude, longitude, district, and state” to identify the spread pattern using a modified reaction-diffusion model (MRD-Model) and Geographic Information System.

Findings

The analysis of the closed population group revealed an initial uneven yet rapidly expanding geographical spread characterized by a high diffusion rate α approximately 0.4503 and a lower reaction rate β approximately 0.0256, which indicated a slower growth trajectory of case numbers rather than exponential escalation. In the latter stages, COVID-19 incidence reached zero in numerous districts, while in others, the reported cases did not exceed 100.

Interpretation

The MRD-Model effectively captured the disease transmission dynamics in the abovementioned setting. This enhanced understanding of COVID-19 spread in remote, isolated regions provided by the MRD modelling framework can guide targeted public health strategies for similar isolated areas.

Funding

This study is Funded by Indian Council of Medical Research (ICMR).