PREDICTION OF THE ENDING OF THE SPREADING OF COVID-19 IN INDONESIA

29/06/2020 Views : 346

Made Sumadiyasa

Nearly three months we are in an uncertainty, especially in an area of social and economy because of the impact of the uncertainty of the spread of co-19 will end. As a result, decision makers/policies often seem hesitant to make decisions. The decision that involves a lot of people needs to think about all aspects that will be influenced by the decision. Decisions/policies taken now can determine the life to come. In the context of the covid-19 pandemic, predictions are needed which can help the decision makers prepare strategic steps in the response to the covid-19 pandemic. With the right prediction when covid-19 will end, we hope the government can make policies that can keep the socio-economic movement of the people.

A few months ago there is a prediction showing a graph that the pandemic corona in Indonesia will end in months of September 2020. By using the data number of accumulated positive confirm covid-19 from early March to the end of May (https://www.kompas.com/covid-19), using a mathematical model of the Gompertz growth approach  obtained graphs as in Figure 1.  From those Figure  appears that the growth of positive confirm Covid-19 at the end of August has started level off and in September 2020 it is estimated that no positive confirm Covid-19. This is clearly seen in Figure 2. The growth rate peaks of positive confirm Covid-19 occurred in mid-April, then declined and ended around the end of September. This is consistent with what was reported previously which shows that the Indonesian graph shows a covid-19 pandemic in theoriticaly ending as a whole on September 23, 2020 (Detik.com).


Figure 1. Positive confirmed growth of Covid-19 data from 4 March – 20 May 2020


Figure 2. Modeling of the positive confirmed Covid-19 growth rate from 4 March 4 – 20 May  2020

Predictions that are made based on mathematical modeling, to get the right modeling accurate data is needed by considering various parameters, such as community dynamics, the amount of data recorded (data from laboratory test results), the level of community vulnerability to viruses. If there is a change in those parameters significantly, it can result in changes in the data so that the modeling becomes changed too.

As happened later, there was a change in policy and resulted in changes in the dynamics of the movement of society without the implementation of strict health protocols. There is an increase in capacity to carry out tests so that the amount of data recorded every day increases. As a result, an increased very sharply of the data positive confirm covid-19 occurred. This affects the modeling, and if using data from 1 April 2020 to mid-June, a predictive picture like Figure 3 and 4 are obtained. From Figure 3 it appears that until March 2021 the curve is still rising. This means that it is estimated that by March 2021 there will still be confirmed Covid-19 significantly. This is made clear in Figure 4, the growth rate is estimated to start to decline in July 2020, but until March 2021 covid-19 is still not over.


Figure 3. Covid-19 positive confirmed growth data from 1 April - 15 June 2020


Figure 4. Modeling of the positive confirmed Covid-19 growth rate from 1 April - 15 June 2020.

From the prediction model, it can be seen that the prediction modeling will change if there is a change in the amount of daily data positive confirm covid-19. This is related to changes in community dynamics and the ability to conduct covid-19 testing. What is needed is an effort to prevent maximized transmission, inhibit transmission by reducing the possibility of inter-human virus transmission. Predictions based on mathematical modeling and objectively aimed data are basically not really exact because to complex, dynamic and heterogeneous world reality.

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