Prerana's note on Demystifying the Yale Study

Prof. (Dr.) Pravin Patkar
CO-FOUNDER & DIRECTOR,PRERANA & HEAD, ANTI TRAFFICKING CENTRE PRERANA

Kashina Kareem
ASSISTANT DIRECTOR, PRERANA

In the month of May 2020, almost 5 weeks into the COVID-19 induced lockdown, researchers from the Yale University, Connecticut and Harvard Medical School, Massachusetts released a research titled – ”The effect of extended closure of red-light areas on COVID-19 transmission in India” recommending extended closure of the Red Light Areas (RLAs) in major Indian cities to prevent the spread of the COVID-19 infection. The subsequent weeks saw an upsurge of news articles on the research report and its staggered recommendations to the Govt. This note is our reflection on the Study, it’s content and recommendations based on Prerana’s three decades of work in the RLAs of Mumbai and Navi Mumbai.

The abstract of the report of this research study (the Report) that has been made available only recently (around June 2020) in the public domain does not have any endorsement from the respective universities. It also does not include any preface or accreditation which are important elements of a formal research study. Despite these facts, the research study and its recommendations seem to have received substantial coverage in the media due to its association with the prestigious academic universities. Read the abstract here

The Model of the Research Study 

The Abstract opens with the assumption, more correctly, the bias of the researchers. ‘Commercial sex work in red-light areas (RLAs) has potential to lead to COVID-19 resurgence….’  which is premature and far from having been scientifically established. Even towards the end of July 2020 and hence certainly when the Report was drafted and released around May 2020, the scientific community did not have enough information and knowledge about the behavior of the virus and the progression of the pandemic. For example, whether being on the anti-retroviral therapy for HIV and AIDS leads to better resistance and higher immunity to getting infected by the COVID-19 virus or does it make the persons living with HIV more vulnerable to contracting the infection or it is neutral to the transmission is yet to be scientifically established. This bias is not peripheral to the Study. On the contrary, it deals with the very core of the public policy the Report is recommending and hence, cannot be ignored.  

Opening, reopening, closing and extended closure of the RLAs’

The Report consistently broaches the subject of ‘opening, reopening, closing and extended closure of the RLAs’. Unlike in the nations where prostitution including organized prostitution is licensed and legalized and hence there exist distinct zones under the zoning policies, India does not have officially earmarked or laid out sex trade/prostitution zones or administratively laid out red light areas. Officially RLAs existed under the laws in port cities and cantonment areas during the British colonial period or pre-independent India. Prostitution (as defined under Section 2(f) of the Immoral Traffic Prevention Act, 1956, popularly called the ITPA) including organized prostitution is illegal in India. It is defined as an act of exploitation and is a punishable offence. Under the ITPA 1956, the RLAs were declared illegal. Hence the basic idea of the closure of RLAs and reopening of RLAs central to the Study simply does not apply to the post-1956 Indian situation. Although there are high concentrations (conglomerations) of the organised sex trade, these are not earmarked or compartmentalized by way of their boundaries. Similarly, the buildings therein are not used exclusively for the sex trade. Off late in Mumbai, more specifically in the past 15 years, the occupancy in the RLA buildings is mixed. There are residents not engaged in the sex trade and there are commercial establishments whose number and proportion to the overall population is increasing over the last decade.

The researchers claimed to have developed a model of COVID19 transmission in RLAs, evaluating the impact of extended RLA closure compared with RLA opening on cases, hospitalization and mortality rates within the RLAs of five major Indian cities. India declared a nationwide lockdown on 24th March 2020 for 21 days. This lockdown was subsequently extended to 3rd May, 17th May and finally to the 31st May. Some states continued the lockdown till June 2020 depending on the rate of transmission of the virus. Nowhere in India were the RLAs under lockdown exclusively. The lockdown was for the entire cities or districts and hence the impact of lockdown is attributable to the overall lockdown. Since there was no RLA specific lockdown the impact on transmission, hospitalization, reproduction, deaths cannot be specifically attributed to the RLAs. Since in India, the sex trade/ prostitution is not licensed, brothels are not registered and since the RLAs are not under zoning policy there is no way to measure such impact exclusively of the RLAs. 

The situation on reopening, besides being fundamentally illogical in the Indian context, is a hypothetical phenomenon as nowhere in any of these places under the study in India, the lockdown was revoked or relaxed, especially considering the period of this Study. The lockdown has only been repeatedly extended. The unlocking has been a very gradual process that started cautiously around June-July and dropped at the first sign of the rise in the reported cases of infection and misuse of the unlocking facility by the public. Similarly, there was no reopening of RLAs in India. Hence there is no empirical basis for this comparison and thus for the model that is the premise of this research. 

Delaying the Peak

The Report claims that the extended closure of the RLAs would benefit the Indian population at large by delaying the peak of COVID-19 cases by 8 to 23 days. The study further makes extremely accurate projections around the delay in peak in different cities and attributes them exclusively to the extended closure of the RLAs. While there are various projections around the peak of COVID-19 cases in various cities and states in the country, we are well aware that this data is also ever-evolving. Back in March, when the lockdown was first introduced in India, there were projections of the peak arriving in the end of May then around June-July. In July 2020, most epidemiologists predicted a peak in infection in late July or early August. Many others currently believe that a national peak is nebulous. The Indian Institute of Public Health, claims that a uniform countrywide peak in COVID-19 cases might not be possible at all. While states like Delhi, could witness the peak by the end of July or early August, states like Tamil Nadu, Maharashtra and Karnataka might experience it around September. Thus, the precise projection of delay in the peak as stated in this research especially back in the early days of understanding and studying the virus and the pandemic, by marginalizing a community is unfounded. 

Authenticity of Data Collection 

The data quoted in this research is specific to the cases, hospitalizations, and mortality rates within the RLAs. Since no State or the other entities involved in data maintenance in India, keep a separate data of transmission of infection, the incidence of hospitalization, deaths and recovery specifically for the RLAs, such empirical analysis is out of question. 

While the data collection of this Study could be considered to have been taken place in April and early May 2020, India was operating in a state of deep ignorance about COVID-19 during these initial months. There is no doubt that the scientific community worked hard and created a fast-growing knowledge base about the virus and the pandemic but it is still far from sufficient to evolve important public policies. During this initial period, there were questions and concerns around the mutation of the virus, vaccination, spread of the infection through asymptomatic persons, rate of transmission, type of treatment, recovery rate and time for different groups, risks of reinfection, etc. During this period, and even today, new treatment regimens are being tried out and are fast changing the recovery period and recovery rate. The response of the state too was very dynamic and in the absence of adequate scientific knowledge base the state administration was also learning everyday with trial and error. Its capacity to deal with the ill health burden of the pandemic was extremely dynamic and evolving. In essence, the situation was extraordinarily fluid and fast evolving.

Under these circumstances it sounds absurd and illogical to come up with a statistical model that predicts the various rates (rate of transmission, reproduction of infection, recovery, deaths, degrees of physiological damage by the infection, etc) that too in a comparative scenario (extended RLA closure Vs. reopening). 

There are several questions about the soundness of the data collection activity under the Research. In the city of Mumbai, the lockdown was taken up quite seriously by most people, of course, with a few exceptions. In fact, the police were blamed for being merciless in enforcing the curfew and the lockdown. There was no separate arrangement for curfew in the conventional areas of high concentration of sex trade (RLAs). It was and continues to be a part of the closure of the city/district. There was curfew declared and assembly of 5 or more persons was banned. Local trains were completely shut down and later opened on a very small scale for the travellers on COVID-19 duty alone, and road transport including public transport was shut down and only partially opened a month later. Certain essential activities like medical services, pharmacies, hospitals, dispensaries and clinics, essential food supplies were allowed with prior permission from the authorities. Banks were allowed to function with only a small proportion of their staff. Almost 4 to 6 weeks after the initial lockdown, other essential services were allowed to run with prior permission and with only a fraction of its staff. The list of essential services was very gradually and cautiously expanded. Some of the relaxations were withdrawn quickly on suspecting misuse by the public. Clinical scientific research and data collection which was a part of the hospitals was allowed. The only outreach activity was the state wide drive for testing of COVID-19 infection. Assembly, processions, and other mobility for festivals, or social visits and functions were completely banned. Physical mobility in public spaces for conducting social research in open society was never a part of the activities allowed under the lockdown and continues to be banned till date.

Speaking specifically of the RLAs of Mumbai it must be noted that all the lanes and by-lanes of Kamathipura and Falkland Rd., covering the two prominent conventional RLAs of Mumbai, were sealed by the police thereby completely blocking the entry of outsiders and exit of insiders. As per our close ground-level observations, the police deeply harbored the bias that the prostituted women may be the prime carriers of the virus and enforced the clampdown very seriously. Most civil society organizations otherwise providing various services to the women and children in the RLAs could only be allowed to distribute food grains after a lot of scrutinies and with limited physical mobility. Hardly any customers could reach the RLAs for sex or otherwise. Considering this backdrop, how could any data collection be carried out for supposedly such a highly predictive research study which in fact requires extremely high precision data? And when it is about a variance of the differential impact in a situation of extended lockdown – closure or reopening then the data would have to be essentially comparative in time and space.

As from the beginning of the month of February 2020, the news of COVID-19 started landing on the shores of India and in most parts of the world except China, Italy, Spain, and parts of USA (where it had already caused havoc) there is no reason to believe that the ‘high precision’ research design was already in operation for gathering the data. We are a part of a highly credible anti-human trafficking civil society organization working in the heart of the RLAs for over 32 years providing comprehensive services on a 24X7 basis including extensive outreach to the RLAs. We were not contacted by anyone for any data collection nor even to gather our impressions or observations by way of formal or informal interview neither did we get to know about any such activity being conducted in the RLAs through the women, children and other civil society organizations that we work closely with.   

At the minimum a study with such objectives would have required a basic comparative model e.g. measuring the impact of the various variables like transmission, hospitalization, recoveries, deaths, reproduction (through contact tracing), across at least two RLAs; one, where the lockdown is relaxed and the other where the lockdown is extended. Such comparative analysis also presumes that the other factors are under control and constant. In the highly fluid and dynamic situation of COVID-19 transmission and lockdown, such presumption is impossible.

The Study claims to have developed an age-structured dynamic model for COVID-19 transmission that claims to quantify the contribution of the RLAs towards the COVID-19 burden in India. For this purpose, the Study segregated the population of each location into the so-called RLA residents – which included both, women in the sex trade and others involved but not soliciting for sex and the general population. These two populations were further stratified into four different age groups. While the age distribution and the relevant data claims to be based on the latest census (2011), adjusted to the current population estimates, the question about the maintenance of such data specific to the RLAs remains. The Study also makes certain assumptions failing to back them up adequately with data or references like the other population in the RLA not soliciting for sex but involved in the sex trade accounts for five times more interactions with the clients as compared to the women soliciting for sex. The estimates and projections on the contact rate seem to have been calculated as the per-capita daily clients from the larger general population who visit the red-light area. While there have been larger debates and discussions around the data of clients approaching the RLAs for sex, this Study conveniently escapes the discourse by not clarifying the reference or source of such data.

Singling out the RLAs and the women in the sex trade

Science is not divorced from common sense. Putting some mathematical equations and formulae can snub people by overwhelming them with scientificity but they cannot pass the test of basic common sense and authenticity. The entire exercise is not only flawed in conceptualization and basic assumptions but starts with a strong bias and capitalizes on the demand for closure of RLAs and the sex trade.

Mumbai’s public transport especially local trains that carry up to the tune of 7 million passengers every day is the highest source of transmission of COVID-19. The trains are so jam-packed with people that a single person is simultaneously in bodily touch with at least 4 other passengers for the entire journey on an average of 20 to 60 minutes, twice every day. Next is the local public bus transport which at the peak hours is characterized by the physical proximity among the passengers. Mumbai’s streets are equally crowded. Gathering of a crowd in Mumbai requires no special reason. A simple routine activity of an excavator digging a roadside gutter is also found entertaining enough by not less than 40 people who would stand and watch how the earthmover is going around. The same is the situation in the vegetable, fish, and grocery shop lines. Besides these instances, a lot of sex trade in Mumbai is outside of the conventional RLAs. There the frequency of contact between the woman and the customer need not be drastically different from that of the RLA based women. 

The fundamentally flawed and non-comparative research design of the Study does not bother to count the impact of these situations on the transmission, hospitalization, reproduction, and death rates. It singles out and targets the RLA based sex trade. Can all these and other such factors not be counted for any share of the impact of transmission of the infection and the resultant deaths? The study claims that by merely extending the closure of the RLAs anything up to 60% of transmission can be prevented. This implies that the rest of the contacts and activities are only capable of causing 40% of the transmission of the virus. This sounds completely contrary to common sense. 

According to a local newspaper, Kamathipura a red-light area in the south of Mumbai was declared to be a green zone around the end of June 2020. Even though Kamathipura (not the RLA exclusively) saw a rapid surge of COVID-19 cases during March and April, with the assistance of the local corporation and volunteers, the spread was curtailed and towards the end of June 2020, the area had not seen any new cases for at least two weeks. According to another newspaper article, Budhwar Peth, a red-light area in Pune has not reported a single case of COVID-19 so far. Even though there were cases being reported from Budhwar Peth, none were from the RLA. 

There were allegations that this Study would be used to influence policy decisions by creating a scare and forcibly evicting the women from the brothels in the RLAs. It is a well-known fact that the real estate developers have been trying to procure prime land in the South of Mumbai. Such a Study, under the current distress of the global pandemic, could result in blocking any kind of popular support to protect the human rights of these women thereby forcibly displacing them to please the land sharks. 

A scientific theory or model acquires predictive power only when it reaches a very high level of accuracy, reliability, validity, and generalizability through explanatory research. In physical sciences and in epidemiology or virology such theories may be existing but they cannot be applicable to the subject matter of the current study for two reasons. Firstly, because the scientists do not understand the COVID-19 virus well enough to club it with the other relatively better-studied viruses and to apply those theories to COVID-19. Secondly, this is not a study of the behavior of a virus it is about the social behavior of human beings and their interactions with public policies. A foundation of a large number of exploratory studies across many variables and in many different conditions is an indispensable precondition of venturing into any explanatory study. In the COVID-19 induced pandemic and lockdown situation, most nations are far from that progress of social sciences or epidemiology.

It is interesting to note that the study has made no attempt whatsoever to understand the depth and degree of indescribable hardships that the prostituted women and their children suffered due to lockdown. Its recommendations to provide alternative livelihoods are anything but informed and certainly a mere lip service. 

The Report of the research study needs to be read by ignoring the mathematical model which confuses and intimidates the reader, thereby escaping relevant fundamental questions on the research study. The uncalled-for formulae and figures make a poor attempt to make up for the huge deficit in terms of common sense and basic knowledge about the Indian context. 

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