The coronavirus pandemic is unprecedented, and has infected 16.8 million in at least 180 countries in seven months. India has reported 1.5 million cases and 34,000 deaths. By April end, 0.78% of India’s 1.3 billion population was infected as per the Indian Council of Medical Research (ICMR) studies. By mid-July, 24% of Delhi’s 20 million population was infected as per the National Centre for Disease Control’s (NCDC) sero-surveillance survey.
Sero-prevalence studies from many countries indicate that the infection numbers are about 20-50 times more than the test positives reported in the same areas. This implies that the number of very mild and asymptomatic cases is much higher, and is not captured by the health system.
Yet, this fast-spreading virus does not infect all the members of an infected person’s family. On an average, only 10-20% of family members develop the infection after one infection in their family. This rate of secondary cases in a close contact in the family is called household Secondary Attack Rate (SAR).
A global literature review we conducted at the Indian Institute of Public Health Gandhinagar (IIPHG) on SAR showed that the rate is variable — from 4.6% to 50%. Infection rates are higher among the spouse or partner of the primary case and elderly members of the family, but it is lower in children. But most studies showed that 80-90% family members do not develop Covid-19 after a primary case is diagnosed in the family.
Early ICMR data indicates SAR in India is 6%, which means that 94% of family members did not develop Covid-19 even when one member tested positive. This is surprising as the virus is infectious and we are told that one can get infected during a brief five-10 minute exposure at public places such as shops, vegetable vendors or banks. Studies have shown that a person with Covid-19 is most infectious two days before symptoms appear. This means a person begins infecting others on an average at least three to five days before being diagnosed, when no one around them at home is using masks or maintaining social distancing.
Family members are in close contact with each other, sleeping, eating and living in close proximity. In spite of this close contact with an infected person, only 10-20% family members get infected as per most studies published in scientific literature globally.
This is surprising for a highly infectious disease. This tells us something about the infectiousness of the virus and individual immunity against disease.
One obvious interpretation is that around 80% people who remain uninfected in a family are resistant or not susceptible to the coronavirus in spite of close contact without any precautions. This contradicts the notion of a highly infectious disease agent. A low SAR rate of 10-20% questions the assumption that everyone is susceptible to the infection because no one has immunity against it.
One competing explanation is that most cases are very mild with a low viral load, which carries a lower risk of transmission. Only 7-15 % of cases have a moderate or high viral load, which leads to the transmission of infection in many others. But such families will be few, and 85% people with mild disease will not have secondary cases in their families.
A similar phenomenon is observed in epidemics caused by other new viruses, such as chikungunya, that saw 1.4 million cases and thousands of deaths in India in 2006. Even then, not all family members were affected and many people in the community did not fall ill even though the mosquitoes that transmit the disease were ubiquitous.
The explanation there also seems to be that many people have resistance to the new infection and individual-centric immunity or resistance plays a critical role in the transmission of the disease in a population even in the case of new infections.
What is the implication of the finding that a large proportion of the population is resistant to Covid-19? British neuroscientist Karl Friston from University College, London, has modelled data from many European countries and proposed a new concept called “Immunological Black Matter”. He suggests that a large proportion of the population is not exposed to the virus or are not susceptible to the infection. The practical implication of this is that with 20-30% infection rates or sero-prevalence in the community, the city or area will start seeing effects of herd immunity as about 50-60% of the population is not susceptible to the infection. It seems this is what is seen in cities such as Ahmedabad (central zone) where the sero-prevalence has reached 28%, and in Delhi where the sero-prevalence has reached 23% in July.
This does not mean that people should stop taking precautions to prevent transmission as social distancing and masks must be used until the epidemic completely disappears. But given the fast spread of this largely asymptomatic infection, other cities will follow the course of Ahmedabad and Delhi and will soon reach effective herd immunity.
Conducting more sero-surveillance in various cities will give a better understanding of the infection prevalence and how far we are from effective herd immunity. We need local epidemiological and public health studies to understand the disease dynamics. The “vocal for local” call by Prime Minister Narendra Modi should also be interpreted to mean generation and use of local data for disease modelling, and not just using global and imported models.
Dileep Mavalankar is director, and Komal Shah is assistant professor at Indian Institute of Public
The views expressed are personal