dc.contributor.author |
Magana-Arachchi, D. |
|
dc.contributor.author |
Wanigatunge, R. |
|
dc.contributor.author |
Vithanage, M. S. |
|
dc.date.accessioned |
2023-05-19T06:16:23Z |
|
dc.date.available |
2023-05-19T06:16:23Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Magana-Arachchi, D., Wanigatunge, R., & Vithanage, M. S. (2022). Can infectious modeling be applicable globally: Lessons from COVID-19. Current Opinion in Environmental Science & Health, 30, 100399. https://doi.org/10.1016/j.coesh.2022.100399 |
en_US |
dc.identifier.uri |
http://repository.kln.ac.lk/handle/123456789/26306 |
|
dc.description.abstract |
Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modeling to achieve the needed forecasts, the best example being the COVID-19 pandemic. Scientists used various models to determine how diverse sociodemographic factors correlated and influenced COVID-19 Global transmission and demonstrated the utility of computer models as tools in disease management. However, as modeling is done with assumptions with set rules, calculating uncertainty quantification is essential in infectious modelling when reporting the results and trustfully describing the limitations. This article summarizes the infectious disease modeling strategies, challenges, and global applicability by focusing on the COVID-19 pandemic. |
en_US |
dc.publisher |
Current Opinion in Environmental Science & Health |
en_US |
dc.subject |
COVID-19 Infectious diseases Infectious modeling Basic reproduction number Prediction |
en_US |
dc.title |
Can infectious modeling be applicable globally: Lessons from COVID-19 |
en_US |