Modern Statistical Methods for Infectious Diseases to Analyse Covid-19 Pandemic Data in Rwanda

Abstract

The corona-virus ailment 2019(COVID-19) took tens of millions of lives and disrupted dwelling requirements at individual, societal, and international levels, causing penalties globally. Understanding its epidemic curve and Spatio-temporal dynamics is indispensable for the development of tremendous public fitness plans and responses and the allocation of resources. Thus, we performed the analysis of the epidemiological dynamics and spatio-temporal patterns of the COVID-19 pandemic in Rwanda. Using the surveillance bundle in R software version 4.0.2, we implemented endemic-epidemic multivariate time sequence methods for infectious diseases to analyze COVID-19 facts with the aid of Rwanda Biomedical Center, under the Ministry of Health, from March 15, 2020, to January 15, 2021. The COVID-19 pandemic came in waves in Rwanda and showed a heterogeneous spatial distribution across districts. The Rwandan authorities answered effectively and successively through the implementation of more than a few health measures and intervention policies to reduce the transmission of the disease. Analysis of the three factors of the mannequin confirmed that the most affected districts displayed epidemic elements inside the area, whereas the impact of epidemic elements from spatial neighbors had been skilled via the districts that surround the most affected districts. The contamination followed the disorder endemic vogue in other districts. The epidemiological and Spatio-temporal dynamics of COVID-19 in Rwanda show that the implementation of measures and interventions contributed appreciably to minimize COVID-19 transmission inside and between districts. This accentuates the essential name for endured intra-and inter-business enterprise and community engagement nationwide to make a certain effective and efficient response to the pandemic.