Loshini Thiruchelvam

After a breakdown notified in Wuhan, China in December 2019, COVID-19 is declared as pandemic diseases. To the date more than 13 million confirmed cases and more than half a million are dead around the world. This virus also attached Malaysia in its immature stage where 8718 cases were confirmed and 122 were declared as death. Malaysia responsibly controlled the spread by enforcing MCO. Hence, it is required to visualize the pattern of Covid-19 spread. Also, it is necessary to estimate the impact of the enforced prevention measures. In this paper, an infectious disease dynamic modeling (SEIR) is used to estimate the epidemic spread in Malaysia. The main assumption is to update the reproduction number Rt with respect to the implemented prevention measures. For a time-frame of five month, the Rt was assumed to vary between 2.9 and 0.3. Moreover, the manuscript includes two possible scenarios: the first will be the extension of the stricter measures all over the country, and the second will be the gradual lift of the lock-down. After implementing several stages of lock-down we have found that the estimated values of the Rt with respect to the strictness degree varies between 0.2 to 1.1. A continuous strict lock-down may reduce the Rt to 0.2 and accordingly the estimated active cases will be reduced to 20 by the beginning of September 2020. In contrast, the second scenario considers a gradual lift of the enforced prevention measures by the end of June 2020, here we have considered three possible outcomes according to the MCO relaxation. Thus, the estimated values of Rt = 0.7, 0.9, 1.1, which shows a rapid increase in the number of active cases. The implemented SEIR model shows a close resemblance with the actual data recorded from 10, March till 7, July 2020. Author summary: Conceptualization, A.A.A; methodology, A.A.A, N.M; validation, A.A.A, N.M; formal analysis, A.A.A; investigation, N.M, A.A.A; resources, G.E.M.A, L.T; data collection, L.T, N.M; writing—original draft preparation, A.A.A, L.T, G.E.M.A, N.M; writing—review and editing, V.S.A, S.C.D, B.S.G, P.S, S.A.B.M.Z, N.M; visualization, N.M; supervision, V.S.A; project administration, V.S.A. All authors have read and agreed to the published version of the manuscript

This study discussed building of sliding windows to analyze the relationship between dengue incidences and weather variables of mean temperature, relative humidity and rainfall, across the timeline. A window sized of 20 was selected and applied to find correlation between dengue incidences and each of the weather variable. A few time lag of zero, two, four, six, and eight is compared and the time lag with best correlation is selected for each weather variable. Study did not found a good insight for analysis using mean temperature and relative humidity. For both these variables, it was suggested dengue incidences is better measured using fluctuation of maximum and minimum values. Analysis using rainfall variable was found to vary across the timeline in magnitude and direction of the correlation. Time lag of eight was found to be the most significant explaining the relationship between dengue incidences and rainfall variable.