How people-centric public health surveillance can help control COVID-19

There is an urgent need to engage with the community to capture human lives, their social and economic demography  

By Mathew George
Published: Monday 11 May 2020
Source: Wikimedia Commons

Public health surveillance must capture epidemiological, behavioural, laboratory and demographic data for effective public health action.

At a time when laboratory tests are playing a crucial role in deciding the fate of each novel coronavirus disease (COVID-19) case, there is an inherent domination of approaches surrounding sample collection for testing without adequately focusing on population characteristics. This is despite the power and potential that laboratory tests hold in their contribution to the existing knowledge of diseases.

This knowledge can increase manifold if it is supplemented with social, demographic, behavioral and other characteristics of the community involved.

There will be diverse utilities for laboratory tests if they are systematically carried out on a large scale. For instance, covering systematically a specific cluster where ‘community spread’ is suspected will help understand the real magnitude of the problem in the community.

For the same tests conducted among those with travel history and their immediate contacts with symptoms, a ‘high-risk approach’ is adopted for early detection of cases and its treatment to prevent spread. Finally, repeat tests are carried out among those who are under treatment to monitor progress.

In the above cases, the first two categories have a ‘population purpose’. The processes involved in sample collection also vary depending on its purpose.

So will be the required institutional mechanism as there is a need to systematically organise sample collection to be coupled with community-based data collection capturing people’s living and working conditions, their health behaviours surrounding the disease under investigation and general socio-demographic characteristics with special emphasis on the possible dynamics of transmission.

This information will allow us to group the samples collected as clusters in specific cohorts to facilitate pooled-testing strategy for effective utilisation of test kits. Additionally, data on people’s illness behaviour, presentation of symptoms according to its severity and related information when supplemented with the lab test results can offer vital knowledge about the disease and its epidemiology in Indian context.

The most critical people-centric knowledge regarding the disease in Indian context is still lacking. It is necessary for effective public health action and needs to be gathered through systematic public health investigations. 

Public health surveillance 

When one examines the context of surveillance for COVID-19, the slogan ‘test, test, test’ emerges to be the most dominant. But there is not enough clarity on the manner testing is done.

The recent experience with antibody test kits and its controversy also reaffirmed the same. The need for supplementing laboratory tests with community-based information for interpreting population pattern was never focused as the purpose of laboratory tests within a dominant biomedical approach confines only to individual diagnostics.

Further, as there was a severe shortage of laboratory test kits in the initial stages, Indian Council of Medical Research directive was to test those persons who had travel history and their immediate contacts with symptoms of fever, cough and sore throat. From there on, surveillance of COVID-19, by default, followed a ‘high-risk’ approach, similar to that of HIV/ AIDS.

It, thereby, failed to capture the true picture of population-level prevalence. Even now, any reliable data on population-level prevalence of COVID-19 across population groups is missing.

Hence, most of the interpretations are either based on the positive cases reported on a daily basis or its proportion to the total number of samples tested, despite knowing its limitations.

Even if one considers the test per million criteria as the denominator, the inferences can go wrong as the sample collection process is conveniently done and does not follow any systematic pattern that represents any specific population. As laboratory-centric public health surveillance emerged stronger, people-centric approach was completely sidelined.

This is obvious when one examines the existing data available of those who have tested positive where a range of information including the occupation pattern and socioeconomic characteristics; the differential contribution of possible sites of transmission; the proportion of symptomatic and asymptomatic patients and a population level prevalence even in the most affected sites are missing.

More than a month into the lockdown, the progress seems to be very slow. Immediate efforts shall be made to capture population level understanding of COVID-19 in at least few pockets where more cases are being reported.

In the Heinsberg district, also known as ‘Germany’s Wuhan’, where the disease originated and had the greatest number of cases, has become the laboratory for COVID-19. It provided all necessary social, behavioral, demographic, epidemiological and treatment-related information necessary for action.

German experts have used it as an opportunity to study the disease in high prevalence districts. These include population-level prevalence in that region, proportion of symptomatic and asymptomatic cases, dynamics of disease transmission and the socioeconomic and demographic characteristics of the affected population, case fatality rate and proportion of hospitalisation.

Way forward

Inferences about epidemic situations will be helpful for public health action only if it has the potential to explain the linkages between human life and its contribution to disease occurrence within a society.

Laboratory tests will only help categorise those affected with the disease, which is necessary but not sufficient. There is an urgent need of a multidisciplinary team of experts engaging with the community to capture the various dimensions of human life, their social, economic, demographic and other characteristics necessary for effective public health action.

This is true for all epidemics, but makes it all the more necessary and inevitable in the case of COVID-19 due to its unique character that poses several limitations in accurately interpreting lab results.

In the context of infectious diseases, reliability of laboratory tests during an epidemic depends a lot on the time of sample collection. It is usually possible to detect the virus immediately after the incubation period, which is the duration human body takes to show symptoms.

In the case of COVID-19, the proxy timelines are difficult to rely upon as most of the cases are ‘imported’, which makes it difficult to know the exact time of the entry of virus. More cases being asymptomatic make it further difficult to infer the exact time of onset of infection.

People-centric public health surveillance thus calls for the need to collect information about the social, demographic, economic, behavioral and epidemiological characteristics of people and understand how these engage with their daily lives and working conditions.

Too much dependency on laboratory tests can result in a ‘microscopic’ view of the problem, thus missing the larger picture.

Historically, public health practice has always been successful with a broader framework even at a time when modern technological advancements were popular. Public health ensures justice to public — as people in a dynamic society, we need to acknowledge the agency of active public as a collective.

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