The second and third waves in India: when will the pandemic be culminated?

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• India experienced a severe surge in COVID-19 cases and deaths in May 2021, reporting 47% of global new cases.
• The nation faced a catastrophic second wave, with over 120 million total cases recorded.

Purpose of the Study:

• To predict the number of positive COVID-19 cases in India using the SIR and fractal interpolation models.
• To approximate the epidemic curve and investigate the duration of COVID-19 waves in India.
• To explore the application of these models for assessing and predicting transmission rates of other epidemics.

Main Methods:

• The study utilizes the Susceptible-Infected-Recovered (SIR) model combined with fractal interpolation.
• Fractal interpolation is applied to estimate the epidemic curve, with vertical scaling factors derived from the SIR model.
• The models are implemented on daily COVID-19 positive case data from India and its provinces (Delhi, Karnataka, Tamil Nadu, Kerala, Maharashtra).

Main Results:

• The combined SIR and fractal interpolation model provides a method for approximating the COVID-19 epidemic curve in India.
• The study enables prediction of forthcoming outbreak trends and investigation into the duration of the second and third waves.
• The methodology offers potential for assessing and modeling transmission rates in other epidemic scenarios.

Conclusions:

• The integration of SIR and fractal interpolation models offers a robust approach for forecasting epidemic trajectories.
• This modeling technique can aid public health strategies by predicting wave durations and transmission dynamics.
• The developed framework is adaptable for analyzing and predicting future outbreaks of infectious diseases.