Academicians from Yale School of Medicine and Harvard Medical School recently released a study on the impact of the closure of red light areas during the lockdown. They also found that Indians are at a much lower risk of contracting COVID-19 if red light areas are kept closed after the lockdown.
Abhishek Pandey, Associate Director, Yale Center for Infectious Disease Modeling and Analysis, tells Outlook that it is extremely important to be cautious about how India reopens everything because any complacency can have disastrous consequences.
Excerpts from the interview: –
According to your study, India could avoid 72% of COVID-19 cases after lockdown by closing red light areas. What’s the basis for this assessment?
In India, there are close to 6,37,500 sex workers as per the National Aids Control Organization (NACO) and over 5 lakh customers visit the red-light areas daily. The study shows if the red-light areas start operating, the disease will spread extremely quickly and infect a very high percentage of sex workers and customers. The high transmission rate is because social distancing is not possible during sex.
How do you look at the progression of the virus in India? Does India have a milder epidemic?
Swift lockdown implemented by India has resulted in a relatively slower growth rate of COVID-19 in India than several other countries such as the United States or Italy. We don’t know yet if India has a milder epidemic. It is extremely important to be cautious about how India gradually reopens everything because any complacency can have disastrous consequences.
We know there is a significant number of asymptomatic infections and the number of reported cases is dependent on testing. Therefore, most countries are under-reporting cases at various degrees. India, in particular, has been relatively slow to scale up their testing.
Do we have an explanation to why some districts are badly affected while some aren’t? For instance, Dharavi, a slum area in Mumbai, where physical distancing is not possible, witnesses low transmission whereas other areas have experienced an outbreak.
We don’t have a clear explanation for this heterogeneity across districts yet. However, potential reasons could include differences in testing, comorbidities in population as well as the effectiveness of physical distancing measures in these regions. For example, in Dharavi, there is likely a far higher number of cases than what we have detected so far. Moreover, the government understands why physical distancing is impossible in Dharavi. 50% of the people under containment in Mumbai belong to Dharavi.
Mitigation strategies are more stringent in Dharavi and may have contributed towards this possible lower transmission. Only with more data, would it be possible to understand these things conclusively.
When can we see the peak and then flattening of the curve?
Whether we will see a spike in cases may depend on how we move forward after the lockdown is over. Given how densely populated India is, it will be crucial for us to maintain physical distancing even after the lockdown is over. Regions and activities that have the potential to exacerbate transmission will have to be kept closed or strictly monitored. Both the timing and magnitude of the peak will be determined by how effectively we scale up testing and conduct aggressive contact tracing.
There are allegations that data is being withheld or not being properly maintained. Your take?
It is hard to say whether data is being withheld or sharing it is not prioritized. However, the lack of data is indeed a major limiting factor for us to contribute significantly towards fighting this pandemic. Accuracy, as well as the utility of model projections, are dependent on the data they use. For example, data on age, gender, comorbidities, hospitalizations, mortality, testing, etc would have allowed us to understand how this pandemic is affecting India. Right now, either some of these data are not being presented at all or they are only presented partially.
Do you think a robust data culture and research ethos will benefit the future?
I think robust data culture and research ethos is not only beneficial for the future, but it is also essential. Hopefully, that is one of the lessons India learns from this pandemic and makes data collection and sharing a priority.