Abstract. This preliminary study is aimed at examining the growth rate of Covid-19 pandemic in Indonesia within a framework of a nation-wide issue. Using spreadsheet, this study models  time-series development of the disease from its early stage in March to the late of June 2020. The study  focuses upon the analysis of three indicators, namely the number of people (with no gender and age separation) confirmly infected, no longer infected, and death, daily reported by govermental authorities to monitor the severe outbreak in the country. Here, the term ‘patient’ for common use in accordance with this spreadout disease is avoided considering that people that are confirmly infected may not be secured with medical treatment in referred hospitals. Instead, we prefer to use another terminology called ‘a case’ throughout the text in this study. A number of classified groups of people widely used in formal reports as well as in society, such as people under observation (ODP), patients suspected (PDP), people with no symptoms (OTG) are excluded as indicators due to difficulties in clear definition hence accurate detection of the number of these groups. Positively confirmed cases are then determined by the results of a Polymerase Chain Reaction (PCR) test on the basis of a swab sampled and are not directly decided by those of an initial rapid test. All the data were collected from primary sources of The Ministry of Health, The Republic of Indonesia and National Agency for Disaster Relief (BNPB). We thus report findings on the effectivity of physical and social distancing policies (PSBB) during different periods of time and the roles of the four likely connected parameters, including community resillience, goverment controls, medical access, and economy recovery in a curve trend generated by spreadsheet. From the day-to-day data acquired for the indicators during a period of four months of data collection presented in three distingushed curve trends, we analyse the growth rate of Covid-19 in Indonesia. Regarding the trends as a logic measure of public health outlook (with indication of continuous Corona disease transmission recently), we then conclude that a combined factors, including ineffective implementation of the policies and community resillience at low levels all make the infectious disease outbreak uncontrollable in some sense.