Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India
The novel SARS-CoV-2 virus, as it manifested in India in April 2020, showed marked heterogeneity in its transmission. Here, we used data collected from contact tracing during the lockdown in response to the first wave of COVID-19 in Punjab, a major state in India, to quantify this heterogeneity, and...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-09-01
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| Series: | Epidemics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1755436521000311 |
| _version_ | 1819028401247223808 |
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| author | Nimalan Arinaminpathy Jishnu Das Tyler H. McCormick Partha Mukhopadhyay Neelanjan Sircar |
| author_facet | Nimalan Arinaminpathy Jishnu Das Tyler H. McCormick Partha Mukhopadhyay Neelanjan Sircar |
| author_sort | Nimalan Arinaminpathy |
| collection | DOAJ |
| description | The novel SARS-CoV-2 virus, as it manifested in India in April 2020, showed marked heterogeneity in its transmission. Here, we used data collected from contact tracing during the lockdown in response to the first wave of COVID-19 in Punjab, a major state in India, to quantify this heterogeneity, and to examine implications for transmission dynamics. We found evidence of heterogeneity acting at multiple levels: in the number of potentially infectious contacts per index case, and in the per-contact risk of infection. Incorporating these findings in simple mathematical models of disease transmission reveals that these heterogeneities act in combination to strongly influence transmission dynamics. Standard approaches, such as representing heterogeneity through secondary case distributions, could be biased by neglecting these underlying interactions between heterogeneities. We discuss implications for policy, and for more efficient contact tracing in resource-constrained settings such as India. Our results highlight how contact tracing, an important public health measure, can also provide important insights into epidemic spread and control. |
| first_indexed | 2024-12-21T05:57:47Z |
| format | Article |
| id | doaj.art-2227ad1459214d6fbc19ccd66fa52503 |
| institution | Directory Open Access Journal |
| issn | 1755-4365 |
| language | English |
| last_indexed | 2024-12-21T05:57:47Z |
| publishDate | 2021-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Epidemics |
| spelling | doaj.art-2227ad1459214d6fbc19ccd66fa525032022-12-21T19:13:48ZengElsevierEpidemics1755-43652021-09-0136100477Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in IndiaNimalan Arinaminpathy0Jishnu Das1Tyler H. McCormick2Partha Mukhopadhyay3Neelanjan Sircar4MRC Centre for Global Infectious Disease Analysis, Imperial College, United Kingdom; Corresponding author.McCourt School of Public Policy and the Walsh School of Foreign Service, Georgetown University, United StatesDepartments of Statistics and Sociology, University of Washington, United StatesCentre for Policy Research, New Delhi, IndiaCentre for Policy Research, New Delhi, India; Ashoka University, Sonipat, IndiaThe novel SARS-CoV-2 virus, as it manifested in India in April 2020, showed marked heterogeneity in its transmission. Here, we used data collected from contact tracing during the lockdown in response to the first wave of COVID-19 in Punjab, a major state in India, to quantify this heterogeneity, and to examine implications for transmission dynamics. We found evidence of heterogeneity acting at multiple levels: in the number of potentially infectious contacts per index case, and in the per-contact risk of infection. Incorporating these findings in simple mathematical models of disease transmission reveals that these heterogeneities act in combination to strongly influence transmission dynamics. Standard approaches, such as representing heterogeneity through secondary case distributions, could be biased by neglecting these underlying interactions between heterogeneities. We discuss implications for policy, and for more efficient contact tracing in resource-constrained settings such as India. Our results highlight how contact tracing, an important public health measure, can also provide important insights into epidemic spread and control.http://www.sciencedirect.com/science/article/pii/S1755436521000311COVID-19SARS-CoV-2HeterogeneityTransmission dynamics |
| spellingShingle | Nimalan Arinaminpathy Jishnu Das Tyler H. McCormick Partha Mukhopadhyay Neelanjan Sircar Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India Epidemics COVID-19 SARS-CoV-2 Heterogeneity Transmission dynamics |
| title | Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India |
| title_full | Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India |
| title_fullStr | Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India |
| title_full_unstemmed | Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India |
| title_short | Quantifying heterogeneity in SARS-CoV-2 transmission during the lockdown in India |
| title_sort | quantifying heterogeneity in sars cov 2 transmission during the lockdown in india |
| topic | COVID-19 SARS-CoV-2 Heterogeneity Transmission dynamics |
| url | http://www.sciencedirect.com/science/article/pii/S1755436521000311 |
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