Analysis of the Worldwide Corona Virus (COVID-19) Pandemic Trend;A Modelling Study to Predict Its Spread

Muhammad Qasim; Waqas Ahmad; Minami Yoshida; Maree Gould; Muhammad Yasir

The copyright holder for this preprint . https://doi.org/10.1101/2020.03.30.20048215 doi: medRxiv preprint focus on providing good diagnostic facilities along with providing remotely accessible health advice, together with specialised treatment for those with severe cases of the disease. As our mathematical model is based on the latest and large scale real-time data and it should provide an additional advantage over the other modelling studies for COVID-19. Secondly, our model was not based solely on mobility data and a large proportion of that data was from the phase of the pandemic when countries had already taken measures and travel bans were in place. The only limitation of our model is that we did not consider the worldwide temperature differences and seasonality of coronavirus transmission. If 2019-nCoV, similar to influenza, has strong seasonality in its transmission, our epidemic forecast might be biased. Furthermore, we did not account for a vaccine to become publicly available to reduce the impact of the pandemic. But even in the absence of a vaccine, human behaviour and the environment itself can alter the likelihood of spread. Hospitals isolate infected people or they may self-quarantine. A further decrease also often occurs as an outbreak matures as people become immune because of previous exposure, reducing the number of susceptible hosts. It has been recently reported that COVID-19 can stay active in aerosol droplets for 3 hours and viable on solid surfaces for 72 hours so new precautionary measures according to this information can reduce viral spread. 11 Further action might include a ban on paper currency notes, a suspension of all cardboard box packed delivery of items and discouragement of human-to-human contact. By using this model world health agencies need to prepare their AID program in advanced for health resources limited countries before the pandemic cause huge damages.