COVID 19 refuses to go away. One thing that it has taught us is that timely advance preparedness is the key to fight it and to lessen its impact, and that the data is the cornerstone of the advance preparedness. Data helps make informed decisions, it helps nip rumours in the bud, and it helps stem panic set-in.
COVID 19 refuses to go away. After wreaking havoc on life, livelihood and liberty during two previous waves, it is back with the same fervour in its third avatar. One thing that it has taught us is that timely advance preparedness is the key to fight it and to lessen its impact, and that the data is the cornerstone of the advance preparedness.
During the first wave, access to health and social services and livelihoods were severely impacted by the COVID 19 epidemic and the resultant national lockdown. Several restrictions were imposed on health services, programmes, clinics and hospitals. Restrictions on transportation barring the movement of essential goods, resulted into a dip in the availability of commodities and products including contraceptives. At the same time, closure of industries, factories, construction activities and other informal sector enterprises resulted in loss of employment and livelihoods. More than 90% informal sector employment is in the informal sector, which has been worst affected by the COVID 19 and the national lockdown. Lakhs of migrants took to their heels to return to their homes because they felt abandoned, left to fend for themselves, vulnerable and at risk in cities and far-away places. Families of these workers and migrants were particularly vulnerable to hunger, lack of access to essential services and eventual poverty. Older persons faced loneliness and lack of support.
Be it the mass exodus of migrants after the national lockdown was announced or the closure of OPDs or non-inclusion of family planning services during the first wave or lack of medical oxygen and beds in the health facilities and associated panic among the people or controversy over the number of deaths during the second wave or lack of care and support for the vulnerable people – all point to the need of data and evidence based planning.
Availability of timely, reliable, and robust information has been long-identified as a pre-requisite for population based pandemic management . Data helps make informed decisions, it helps nip rumours in the bud, and it helps stem panic set-in. This is the one big lesson from the COVID 19. Data in general and population data in particular on the vulnerable population groups and their needs (health and others) are needed in all the three stages of the pandemic:
- Planning stage
- Response stage
- Mitigation and recovery stage
Large as well as big population data could help in planning stage by pointing out the presence of the vulnerable population groups, their locations, population density, transportation practices and other cultural factors/habits. Data on ‘needs of communities of colour, children, pregnant women, and populations at increased risk of serious complications’ help in planning for health, social, economic and other essential services. This could also help us in identifying the resources within and beyond communities, which could be mobilized to mount a quick emergency response. For example, a group of researchers used population large and big data and developed a predictive model for COVD 19; using just five demographic factors they were able to predict just five risk factors can predict between 47% and 60% of variation in COVID-19 prevalence in U.S. counties: population size, population density, public transport, voting patterns and percent African American population . The group showed that ‘additional planning based upon cultural and demographic factors can help predict how outbreaks could progress. It can also reveal which people may be most vulnerable’.
Population-based management (PBM) decision making in pandemics is a necessary tool for seasoned experts in preventing virus transmission, limiting morbidity and mortality in settings of limited resources, and attenuating the economic and social effects of the pandemic . PBM has to be thought of and designed in advance because ‘developing the operational relationship between conventional health care and PBM at the time of a pandemic is too late’ . In such a situation, ‘PBM teams would work collectively to develop a robust, data-driven core capacity of information based on the identification of multiple critical population-based demographic sources required for prevention, preparedness, response, recovery, and rehabilitation’ .
Hence, in brief, we need to invest in and strengthen our emergency response systems so that in facing such a crisis in future, we are able to respond effectively and without affecting the routine health services and commodity supplies. We need to strengthen capacities to use population and administrative data to forecast needs of different population groups for different services and commodities up to ward and village levels to ensure smooth supplies of services and commodities. Not only the availability of data but its availability and capacity to use at the local level have to be ensured.
 Burkle FM Jr., Bradt DA, Ryan BJ. Global Public Health Database support to population based management of pandemics and global public health crises, Part I: the concept. Prehosp Disaster Med. 2020;00(00):1–10. (pp. 3)  USA, ‘National Strategy for the COVID-19 Response and Pandemic Preparedness’. President’s Office; January 21, 2021  Bentley, Alexander R., ‘How to use statistics to prepare for the next pandemic’. GCN; May 18, 2021; https://gcn.com/data-analytics/2021/05/how-to-use-statistics-to-prepare-for-the-next-pandemic/316111/  Burkle FM Jr., Bradt DA, Ryan BJ. Global Public Health Database support to populationbased management of pandemics and global public health crises, Part I: the concept. Prehosp Disaster Med. 2020;00(00):1–10. (pp. 5)  Burkle FM Jr., Bradt DA, Ryan BJ. Global Public Health Database support to populationbased management of pandemics and global public health crises, Part I: the concept. Prehosp Disaster Med. 2020;00(00):1–10. (pp. 6)  Burkle FM Jr., Bradt DA, Ryan BJ. Global Public Health Database support to populationbased management of pandemics and global public health crises, Part I: the concept. Prehosp Disaster Med. 2020;00(00):1–10. (pp. 7)
YouTube Video: #PopulationAndDevelopment | E1 | Population Data and Pandemic Preparedness | Panel Discussion
About the Author
Devender Singh is the Former National Program Officer (Population & Development), UNFPA India (2015- 2021) and a Visiting Senior Fellow at IMPRI.
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