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 Table of Contents 
Year : 2020  |  Volume : 9  |  Issue : 10  |  Page : 5404-5405  

Super-spreader resurgence in COVID-19: Past encounters and future repercussion

1 Department of Medicine, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
2 Director and CEO, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India

Date of Submission07-Jun-2020
Date of Decision09-Sep-2020
Date of Acceptance17-Sep-2020
Date of Web Publication30-Oct-2020

Correspondence Address:
Dr. Mahendra Kumar Garg
Room No. 40, OPD Block Ground Floor, Department of Medicine, All India Institutes of Medical Sciences Jodhpur, Rajasthan
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jfmpc.jfmpc_1112_20

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How to cite this article:
Kumar D, Meena DS, Garg MK, Misra S. Super-spreader resurgence in COVID-19: Past encounters and future repercussion. J Family Med Prim Care 2020;9:5404-5

How to cite this URL:
Kumar D, Meena DS, Garg MK, Misra S. Super-spreader resurgence in COVID-19: Past encounters and future repercussion. J Family Med Prim Care [serial online] 2020 [cited 2021 Jul 31];9:5404-5. Available from: https://www.jfmpc.com/text.asp?2020/9/10/5404/299343

To the Editor,

Initial epidemiological investigations and contact tracing from India suggested that there was out of proportion of cases of coronavirus disease-2019 (COVID-19) linked to vegetable vendors, dairy booths, and grocery stores in different cities. These incidences resurfaced the role of super-spreaders. In epidemiology, super-spreaders are the infected individuals in the susceptible population who disproportionately infect more persons compared to others. Initial consensus based on epidemiological studies was that each person in infected population has equal chance to transmit the disease to others. Basic reproductive number (R0) is the fundamental tool to measure this disease transmission; however, there are lot of inter-individual disparities in infectiousness observed inside a susceptible population which compelled the epidemiologist to look beyond R0. The advent of 20/80 rule also imitates this hypothesis where 20% of the infected person contributes for nearly 80% of the disease transmission.[1] Probably, the first known super-spreader in history was “Typhoid Mary,” responsible for infecting at least 122 individuals, 5 of whom died from enteric fever.[2] The other notorious super-spreader events were documented during MERS-CoV, SARS CoV, and current COVID-19 outbreaks. “Patient 31” from South Korea, who participated in a religious gathering, contributed to the exponential rise in number of cases.[3]

The reason for this heterogeneous transmission of disease is still unclear. Host-pathogen interaction, environmental, occupational, and behavioral factors can influence this transmission.[2] Virulent nature of virus (due to mutation) and co-infection are important factors for increased viral shedding. Among host-related factors, genetic susceptibility, immunosuppression, low level of pre-existing immunity, duration and type of contact can determine the super-spreader events. Population density and air recirculation in enclosed spaces are major settings for COVID-19 super-spreader. Lack of adherence to public health advice, inter-hospital patient transfer, underdiagnosis, religious gatherings, frequent air travel, and bypassing geographical barriers are the common practices involved in super-spreader events across the world. The recognition of these potentially modifiable risk factors is fundamental difference between a disease limited to clusters, epidemic, or converting into a full-blown pandemic.

Currently, all super-spreaders have been identified only by retrospective epidemiological investigations. Studies based on animal model that can replicate a disease seen in humans could be vital to predict the infectiousness of individual. Genome-wide association studies (GWAS) involving super-spreader could provide insight to genetic background of these patients, though feasibility and cost-effectiveness of these studies on large scale population are remains to be seen. Walker et al. described the utility of GWAS in identification of super-spreaders in  Mycobacterium tuberculosis Scientific Name Search tbreak.[4] Retrospective comparison of super-spreaders with other patients for characteristics (age, sex, clinical presentation, co-morbidities, environment, and their behavior) can help in better understanding of super-spreader phenomenon. Isolation of virus from known super-spreaders and their genomic analysis for any shared mutation can also provide evidence for enhance virus shedding.

The definition of super-spreaders should not be confined to a person and must include other variables like groups, policies, events or a setting which can shape a course of disease transmission. At the same time, efforts should be made to avoid stigmatization and social ostracism of these patients. There should be a clear roadmap to contain super-spreaders in population. Epidemiological analysis and individualistic approach focusing 20% of highly infectious patients could save lot of time and resources for pandemic preparedness plans.[5] Super-spreaders become an important facet in infectious disease management, lesson learned from past pandemics and their application in the formulation of public health policies can determine the future course of outbreak containment and mitigation.

Financial support and sponsorship

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflicts of interest

There are no conflicts of interest.

  References Top

Woolhouse ME, Dye C, Etard JF, Smith T, Charlwood JD, Garnett GP, et al. Heterogeneities in the transmission of infectious agents: Implications for the design of control programs. Proc Natl Acad Sci U S A 1997;94:338-42.  Back to cited text no. 1
Stein RA. Super-spreaders in infectious diseases. Int J Infect Dis 2011;15:e510-3.  Back to cited text no. 2
Her M. How is COVID-19 affecting South Korea? What is our current strategy? Disaster Med Public Health Prep 2020;3:1-3.  Back to cited text no. 3
Walker TM, Ip CL, Harrell RH, Evans JT, Kapatai G, Dedicoat MJ, et al. Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: A retrospective observational study. Lancet Infect Dis 2013;13:137-46.  Back to cited text no. 4
Lloyd-Smith JO, Schreiber SJ, Kopp PE, Getz WM. Superspreading and the effect of individual variation on disease emergence. Nature 2005;17:355-9.  Back to cited text no. 5


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