A basic analysis on Covid-19 Data in Sri Lanka

COVID-19 is a new illness that can affect the lungs of person which has now spread in 205 countries in different intensities. The number of total cases vary from 215,300 in USA to one in Papua New Guinea. Sri Lanka ranks at 105.  COVID19 is caused by a virus known as coronavirus.  There is still no vaccine or cure for it.  In this article a few analyses are carried out on COVID19 data in Sri Lanka which can be used for some policy decisions

Trend of Daily COVID New Cases

Based on the data on 01 April, in almost all highly infected countries the daily variability of the new covid19 cases has been increasing exponentially (Figs, 1-3). In contrast, the temporal variability of the new cases for the same period in Sri Lanka is totally different from other countries. It has been slowly increasing exponentially up to 17 March and then has been decaying with an exceptional of 20 on 31 March (Fig. 4).  These results confirm that spread of covid_19 will die off in few months’ time and the probability of spreading to community level is almost zero as so far we have identified individual level and extremely few cases on family level.

Impact of Climate on COVID19

Many studies have shown that high temperature and high humidity reduce the transmission of COVID19.  Transmission of COVID19 was highly efficient at 5°C but was blocked or inefficient at 30°C. Dry conditions (20% and 35% RH) were also found to be more favorable for spread than either intermediate (50% RH) or humid (80% RH) conditions. A very recant study based on temperature and relative humidity using 14 countries claimed that an increase of one degree Celsius and 1% relative humidity increase substantially lower the virus transmission.

An indicator known as, “R naught” (R0) which is used by epidemiologists to estimate the individuals that each infected person will transmit.  In other words, R0 tells the average number of people who will catch a disease from one contagious person. Recent studies further claimed that in cold dry weather, of coronavirus is between 2 and 3, and for every degree Celsius increase and every percent relative humidity increase, R0 reduces by 0.0383 and 0.0224 respectively. Thus, it is obvious that the expected value of R0 in Sri Lanka (300C and 80% RH) can be between 1.5 to 0.8.  However, it is better to compute proxy value for R0, based on Sri Lanka data,

Expected Number of COVID19 Cases

Pattern of Covid19 outbreak is explained by daily by almost all media through the Ministry of Health. Recently, it has been mentioned that 500 infected individuals are circulating within the population by 18th March and those would have had a total of 19,000 contacts (19531), based on R0 as 2.5.  However, I also computed the expected number of infected cases for different R0 values assuming initial value on 18th March as 500. This computation can be easily done using basic properties on geometric progression in arithmetic (Table 1).

Though it says, cases of COVID-19 that fly under the radar without being diagnosed which appear to fuel the rapid spread of the disease, we must get a reasonable value.  Almost all the cases we used to take for quarantine either in hospitals or other places are not positive cases. Further, those who self-quarantine are almost not positive cases. Since we have found only 144 cases by 1 April   (and 51 on March 18),  I took liberty to compute COVID19 contact for different Ro taking the initial value on 18 March  as on 1.5*144 =216 (table 2).