The reliability of statistics and numerical data is crucial in order to ensure accurate information, particularly during a pandemic
While numbers don’t lie, they can definitely mislead people with half-truths. The reliability of statistics and numerical data is crucial to ensure accurate information. Unreliable numerals are arrived at by modifying the figures/values with a motive to portray an improved status or may result from subjective interpretation of data, negligence/ignorance of existing bias in the data collection process or when mathematical amateurs handle important data. Inside locked doors, 1.3 billion Indians have been looking at numbers on screens and newspapers to fathom the country’s Corona status. Over 18 per cent of the Indian population is vulnerable to infectious diseases. Hence, we have reason to fear an exponential spike in Covid-19 cases and deaths. With a testing rate as low as about five lakh (total tests done) in a population of 1.3 billion, we can only hope that the available numbers of the confirmed and cured cases and deaths give the real picture and not lull us into a false sense of having the “pandemic under control.”
The first line of defence against any pandemic is surveillance: Monitoring humans/animals to spot outbreaks and contain them and in the process, collect meaningful data. A laboratory test is the window to the pandemic without which we have no way of understanding the disease load. While we must prioritise testing of the critically ill, by leaving out patients with respiratory disorders/flu symptoms in a hospital, we are missing the chance of testing potential cases. People from marginalised sections of society may not have the same access to testing as someone from the middle/upper class. This may lead to fear/distrust in hospitals/healthcare centres and be a deterrent in their seeking further care or testing. This is a recipe for undercounting and keeping the disease burden invisible in the country.
In Mumbai, about 80 per cent of the Corona deaths happened within a few hours to a day, following hospital admissions. In contrast, the observed median time from admission-to-death in China is 16 days and in the US for non-ICU and ICU patients the averages are 9.7 and seven days respectively. Thus Mumbai’s figures prove delayed testing, just before or after death. They also throw light on how quality data can underscore important points to enable good strategy decisions and crisis response, without which individuals/authorities cannot learn whether measures adopted against the pandemic are working or not. Laboratory tests detect active infections, past infections, immunity status of people and herd immunity in communities. Quality data of the epidemic would be — if the published number is of tests performed or individuals tested (considering one individual may need more than one test), whether negative results are included, whether pending results are included and so on. All these put together will clarify whether the growth of cases is real or only reflects the expanding degree of surveillance/number of tests conducted or if the parameters for data collection are not well sorted. To date, with liberal testing yet to pick up, all eyes are on the rapid serology tests. These tests can decipher results in minutes, are cheaper (than the molecular test — RT-PCR) and can effectively screen blood for public health management purpose though they are not confirmatory in nature and hence not used for clinical practice. Rapid tests will help screen a large percentage of people and if we know that a good chunk of our population has developed antibodies to the virus, it may help authorities allow for less-restrictive measures or staggered lifting of social distancing measures. These tests can be added to routine blood draws that all phlebotomists do regularly with no additional trouble to the patient.
Hospitals are keen on serology tests which could help them identify which healthcare workers have developed a level of immunity already. If there is a batch of say 10 technicians extracting samples and five were immune, the hospital administration could assign them duties and keep the laboratory running. The Coronavirus is here and will surely spread as there is no vaccine or proven cure. At 1.28 per cent of the Gross Domestic Product (GDP), India’s public expenditure on healthcare is the lowest globally (against 17 per cent in the US, 9.8 per cent in the UK and 1.68 per cent in Sri Lanka). Our healthcare system is patchy and we are in no position to cope with this new crisis if it hits us head-on in the coming months.
India has not been able to deal with common infectious diseases like tuberculosis (TB), leprosy, HIV/AIDS, let alone a novel virus of a highly contagious nature. The yearly death toll of TB is 1.5 million, HIV/AIDS is 69,000 besides an ever-increasing number of non-infectious disease morbidities ranging from cancer to cardiac diseases. With a reproductive number or RO of over 2.5, Covid-19, if left to sweep through our population of 1.3 billion, will infect 84.5 million and kill 1.17 million people. With a string of Covid-19 hotspots staring at us, surveillance combined with mass screening must now exist along with quality data collection. There are genuine capacity issues but the Government needs to build it with dedicated funding, perhaps as part of the next stimulus package.
(The writer is an author and a doctor by profession)