Unfolding trends of COVID-19 transmission in India: Critical review of available Mathematical models

Authors

  • Komal Shah Indian Institute of Public Health Gandhinagar, Gandhinagar
  • Ashish Awasthi Public Health Foundation of India, Gurgaon https://orcid.org/0000-0002-9308-9782
  • Bhavesh Modi GMERS Medical College, Gandhinagar, Gujarat
  • Rashmi Kundapur K.S. Hegde Medical Academy, Nitte University, Mangalore
  • Deepak Saxena Indian Institute of Public Health Gandhinagar, Gandhinagar https://orcid.org/0000-0003-0563-4259

DOI:

https://doi.org/10.47203/IJCH.2020.v32i02SUPP.006

Keywords:

COVID-19, Transmission, Mathematical Models

Abstract

Background: There is a surge in epidemiological modeling research due to sudden onset of COVID-19 pandemic across the globe. In the absence of any pharmaceutical interventions to control the epidemic, nonpharmaceutical interventions like containment, mitigation and suppression are tried and tested partners in epidemiological theories. But policy and planning needs estimates of disease burden in various scenarios in absence of real data and epidemiological models helps to fill this gap. Aims and Objectives: To review the models of COVID-19 prediction in Indian scenario, critically evaluate the range, concepts, strength and limitations of these prediction models and its potential policy implications. Results: Though we conducted data search for last three months, it was found that the predictive models reporting from Indian context have started publishing very recently. Majority of the Indian models predicted COVID-19 spread, projected best-, worst case scenario and forecasted effect of various preventive measurements such as lockdown and social distancing. Though the models provided some of the critical information regarding spread of the disease and fatality rate associated with COVID-19, it should be used with caution due to severe data gaps, distinct socio-demographic profiling of the population and diverse statistics of co-morbid condition. Conclusion: Although the models were designed to predict COVID spread, and claimed to be accurate, significant data gaps and need for adjust confounding variables such as effect of lockdown, risk factors and adherence to social distancing should be considered before generalizing the findings. Results of epidemiological models should be considered as guiding beacon instead of final destination.

Downloads

Download data is not yet available.

References

Virulence 4:4, 295–306; May 15, 2013; c 2013 Landes Bioscience accessed on 3 April 2020

Dimitrov NB, Meyers LA. Mathematical approaches to infectious disease prediction and control. InRisk and optimization in an uncertain world 2010 Sep (pp. 1-25). INFORMS.

Piazza NI, Wang H. Bifurcation and sensitivity analysis of immunity duration in an epidemic model. International Journal of Numerical Analysis and Modelling, Series B, 4 (2), 179. 2013;202.

Siettos, Constantinos & Russo, Lucia. (2013). Mathematical modeling of infectious disease dynamics. Virulence. 4. 10.4161/viru.24041.

Dimitrov NB, Meyers LA. Mathematical approaches to infectious disease prediction and control. InRisk and optimization in an uncertain world 2010 Sep (pp. 1-25). INFORMS.

Choisy M, Guégan JF, Rohani P. Mathematical modeling of infectious diseases dynamics. Encyclopedia of infectious diseases: modern methodologies. 2007:379.

Masuda N, Holme P. Predicting and controlling infectious disease epidemics using temporal networks. F1000prime reports. 2013;5.

Keeling MJ, Rohani P. Modeling infectious diseases in humans and animals. Princeton University Press; 2011.

Barthélemy M, Barrat A, Pastor-Satorras R, Vespignani A. Dynamical patterns of epidemic outbreaks in complex heterogeneous networks. Journal of theoretical biology. 2005;235:275.

Moher D, Liberati A, Tetzlaff J, Altman DG, Altman D, Antes G, Atkins D, Barbour V, Barrowman N, Berlin JA, Clark J. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (Chinese edition). Journal of Chinese Integrative Medicine. 2009 Sep;7(9):889-96.

Mandal S, Bhatnagar T, Arinaminpathy N, et al. Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach. The Indian journal of medical research. 2020.

Singh R, Adhikari R. Age-structured impact of social distancing on the COVID-19 epidemic in India. arXiv preprint arXiv:2003.12055. 2020.

ICMR initiates study to predict the rate of Covid-19 infections in India. Available from: https://economictimes.indiatimes.com/industry/healthcare/biotech/healthcare/icmr-initiates-study-to-predict-the-rate-of-covid-19-infections-in-india/articleshow/74768015.cms?from=mdr. [Last accessed 26 March 2020].

Covid-19: Mathematicians, too, chip in to decode the pandemic. Available from: https://www.thehindubusinessline.com/news/science/covid-19-mathematicians-too-chip-in-to-decode-the-pandemic/article31155268.ece#. [Last accessed 26 March 2020].

Covid-19 rise and spread with specific predictions till 1st April for India and US. Available from: https://www.analyticsinsight.net/covid19-rise-and-spread-with-specific-predictions-till-1st-april-for-india-and-us/. [Last accessed 30 March 2020].

Shrivastava SR, Shrivastava PS. Resorting to mathematical modelling approach to contain the coronavirus disease 2019 (COVID-19) outbreak. Journal of Acute Disease. 2020;1:49.

COVID-19 can only be fought at the grassroots with awareness: Jayaprakash Muliyil. Available from: https://www.cnbctv18.com/healthcare/covid-19-can-onlybe-fought-atthegrassrootswith-awareness-jayaprakash-muliyil-5601541.htm. [Last accessed 5 April 2020].

Coronavirus: How many cases will India see? Here's one expert's best-case prediction. Available from: https://www.indiatoday.in/india/story/coronavirus-cases-india-covid-19-ramanan-laxminarayan-interview-1658087-2020-03-21. [Last accessed 26 March 2020].

Predictions and role of interventions for COVID-19 outbreak in India. Available from: https://medium.com/@covind_19/predictions-and-role-of-interventions-for-covid-19-outbreak-in-india-52903e2544e6. [Last accessed 26 March 2020].

Covid-19 India: State-level Estimates of Hospitalization Needs. Available from: https://cddep.org/wp-content/uploads/2020/04/Covid.state.hosp.pdf. [Last accessed 5 April 2020].

The Viral Explosion: A District-Wise Projection Map For Covid-19 In India. Available from: https://swarajyamag.com/science/the-viral-explosion-a-district-wise-projection-map-for-covid-19-in-india. [Last accessed 5 April 2020].

A prediction model for COVID-19. Available from: https://www.thehindu.com/opinion/op-ed/a-prediction-model-for-covid-19/article31092695.ece. [Last accessed 25 March 2020].

Goli S, James KS. How much India detecting SARS-CoV-2 Infections? A model-based estimation. medRxiv/2020/059014. 2020.

India missed the bus on testing. It should lock down now, 3 weeks later it wont work. Available from: https://www.youtube.com/watch?v=2HvAWGuiyfE. [Last accessed 10 April 2020].

Coronavirus India cases and deaths: Best or worst, this online epidemic calculator shows Covid-19 projections. Available from: https://www.indiatoday.in/technology/features/story/covid-19-cases-and-deaths-in-india-this-online-epidemic-calculator-shows-all-projections-1660613-2020-03-28. [Last accessed 10 April 2020].

Sanche S, Lin YT, Xu C, Romero-Severson E, Hengartner N, Ke R. High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2. Emerging infectious diseases. 2020;26.

Xiaolu Tang, Changcheng Wu, Xiang Li, et al. On the origin and continuing evolution of SARS-CoV-2, National Science Review. 2020. nwaa036.

The updates on COVID-19 in Korea as of 11 April. Available from: https://www.cdc.go.kr/board/board.es?mid=a30402000000&bid=0030&act=view&list_no=366810&tag=&nPage=1. [Last accessed 11 April 2020].

Gustafsson LL, Lindstrom B, Grahnen A, Alvan G. Chloroquine excretion following malaria prophylaxis. British journal of clinical pharmacology. 1987 Aug;24(2):221-4

Downloads

Published

2020-04-20

How to Cite

1.
Shah K, Awasthi A, Modi B, Kundapur R, Saxena D. Unfolding trends of COVID-19 transmission in India: Critical review of available Mathematical models. Indian J Community Health [Internet]. 2020 Apr. 20 [cited 2024 Mar. 28];32(2 (Supp):206-14. Available from: https://www.iapsmupuk.org/journal/index.php/IJCH/article/view/1460

Issue

Section

Review Article

Most read articles by the same author(s)

<< < 1 2