When Covid's first wave saw exponential infection growth, statistics and graphs demonstrated striking similarities among urban areas worldwide. In contrast, rural regions consistently exhibited lower infection rates throughout the pandemic.
To illustrate this with a personal anecdote, I know someone who lives in a tiny village on a ranch (population: ~30), and they have reported seeing zero Covid cases, having interacted with around 50 other people over the last four years. I think this underscores the role of population density in virus transmission.
Maybe Indians have less contact with wildlife (due to different settlement patterns, or religious or cultural restrictions on eating wild animals?), or less average physical mobility (more expensive and inconvenient long-distance transportation), or a climate less conducive to certain modes of virus transmission?
A smaller fraction of the population working or commuting in huge indoor spaces?
Maybe (contrary to Americans' intuition) Chinese public health surveillance is both more effective and more transparent than Indian, leading to a measurement bias because some disease outbreaks that arise in China get better-documented?
If I were working on the problem "how can we reduce the frequency new very dangerous viruses are introduced" I would pay attention to this aspect.
I thought the most likely origin of Covid-19 is a lab leak (at least according to the latest from the DOE and the FBI), likely from gain-of-function research gone wrong?
See for example this recent analysis:
Well, specifically, they assessed with "low confidence" that the "most likely" source was a lab leak. Meaning they think the wet market theory is less likely, though also with low confidence.
I do note in the analysis you linked that the authors admit to unusual circumstances around the data they used, and that the source of the data is the Chinese CDC. Given the obvious incentive on the part of the Chinese government to disclaim a lab leak, I'm hesitant to take this as conclusive evidence.