A Data Driven Decision Making and Contract Tracing App for Organizations to Combat COVID-19

Abstract

In this paper we review the threat posed by the COVID-19 pandemic, the justification for the elimination strategy adopted by New Zealand, and some of the actions required to maximize the chances of success. During the current COVID-19 pandemic, there have been many efforts to predict the infection cases, number of fatalities, and other medical indicators, using a range of statistical or epidemiological models. During the current COVID-19 pandemic, there have been many efforts to forecast the infection cases, deaths and other medical indicators including hospital capacity calculation, with a variety of predictive epidemiological models. These forecasting projects have influenced policies in some countries. However, the prediction of the COVID-19 pandemic as a 'wicked problem' is uncertain by nature. The uncertainty is deep-rooted in the many unknown unknowns about the communicable virus itself and the complexity, heterogeneity and dynamism of human behaviors, government interventions and testing protocols. As there are no set standards between and sometimes within the countries, it makes it a 'wicked problem', nearly impossible to predict. The wicked and uncertain nature of this pandemic makes the aim for prediction accuracy deceptive. Herein, we propose to be cautious about the intent for 'accurate' predictions or models. Instead of making inaccurate predictions let us try to understand the data that is available to us to explore the significant indicators of the uncertainty. Such indicators are expected to make the planning and policy more 'future-informed' and possibly introduce and guide pre-cautionary actions now to shape the real future. Also, we have proposed here a Power Apps-based app for organizational users to do a check in on their known location(s) to facilitate contact tracing if needed in an event of Novel Coronavirus suspected case as the countries move between different lockdown levels.