Background: The COVID-19 pandemic was expected to affect India severely; cases rose exponentially from May-June 2020, but around mid-September reached their peak and started declining. It showed a sign of the wave’s completion by the end of January 2021. This decline was not predicted by any models and the authors have not come across any explanation. Winter seasonality of influenza and similar viruses is well known and observed fact and that it has a direct correlation to the colder temperatures as well as lower humidity. Similarly, in low humidity, viruses are most viable, and they become ineffective as the humidity increases and reaches its maximum extent. This article hypothesizes and tries to explain the cause behind the first major decline and shows the subsequent rise of the second wave, and one short low humidity period followed by a high humidity period between the first and second waves.
Methods: The humidity cycles in India were studied to find high and low relative humidity periods, which then corresponded to the daily cases in the country (macro-level), region (mid-level), and smaller regions (micro-level).
Results: A definite correlation was observed between Monsoon-induced humidity and the incidence rate decline. This happens in 8 to 10 weeks. Incidence rates start declining about 4 weeks after the peak humidity is reached in a particular region. A decrease in humidity below 65% or 55% or lower causes an increase in the case increase/uptrend in about 3-4 weeks.
Conclusion: COVID-19 has a seasonal peak in India, peaking in the middle of the monsoon season around mid-September and reaching its lowest levels in January-February. As humidity drops from February to June/July, a trend reversal and sharp rise are expected. The subsequent wave/case peak would be expected to be seen around mid-September 2021.