OJ Watson Profile picture
23 Apr, 22 tweets, 7 min read
Our report on the largely unobserved COVID-19 epidemic in Damasucs was just published in @natcomms.

I don't like sharing my publications but this one I a really proud of. Why? Well over a year has passed and it still is shocking how much mortality has been missed. A Thread
The results have not massively changed since the initial report last September. For an overview see:

The main difference is we used the Facebook obituary notifications data set again to show that the "uptick" in mortality reported during Winter 2020 was not accompanied with a large increase in excess mortality.
This is most likely due to:

1. Substantial immunity after the first wave limiting the size of second wave.
2. Better testing improving what proportion of deaths are recorded.
However, this study was the first to change how I view COVID-19 mortality reporting. The current toll of >3 million deaths is a considerable under-estimate and I suspect it is closer to 10 million than 3 million. Why?
1. Excess mortality in areas we have it are pretty convincing of large levels of under-reporting, with often countries with very high reported burden (Latin America, South Africa, Russia) reporting between 1 in 5 to 1 in 2 deaths.
Also important to highlight here that unreported COVID-19 mortality occurs in all income settings. Spain, USA, Portugal, Italy all had missed COVID-19 mortality at the beginning of their epidemics.
2. Locations that don't have excess mortality, often lower income settings, are showing anywhere between 1 in 100 and 1 in 10 deaths being reported at the peak of epidemics. These estimates also require considerable investigative efforts leveraging novel data source. E.g:
- Satellites of cemeteries in Aden, Yemen: 1.25% deaths reported. medrxiv.org/content/10.110…
- Social media surveys of symptomatic prevalence in combination with molecular and serological surveillance in Khartoum, Sudan: 3% (2% - 5% range) deaths reported. imperial.ac.uk/mrc-global-inf…
- Postmortem PCR for COVID-19 infection in Lusaka, Zambia. ~8% deaths reported. Importantly 72.8% of deaths occurred in the community and not in a healthcare facility. None of these deaths were tested. Only ~1/4 in facilities were tested. medrxiv.org/content/10.110…
- COVID-19 Funeral burial patterns in Jakarta, Indonesia. 25% deaths reported. medrxiv.org/content/10.110…
Why share all this gloom? Because it is really heartbreaking to see the situation in India unfold, with crematorium reports showing massive gaps between reported deaths and COVID-19 cremations:
And yet only a few months ago, there was a really unhelpful discussion occurring where the end of India's first wave was being used as an example of baffling scientists and to draw a contrast against Western epidemics - likely contributing to complacency and the current wave.
But there was evidence of under-reporting in the first wave. Anywhere again between 1 in 5 () to 1 in 2 deaths (bbc.co.uk/news/world-asi…) were reported during the first wave, which help explain the epidemic. See also for IFR/sero
COVID-19 coverage has become increasingly political and country comparisons have been frequently used to essentially shame governments and place blame. But they have created a very toxic environment where attention is diverted away from actually understanding the true burden.
And why is that damaging? I fear that future investment in health surveillance will be based on official reported COVID-19 deaths, further widening the gap in health surveillance. We have already seen the moral failure in terms of global vaccine allocation.
And roll on the next pandemic we will be having the same toxic debates, again with no data to show where transmission is really occurring, how severe the pandemic is in different regions and where vaccination needs to be prioritised.
But now for an optimistic finish. There are data sources out there. This Damascus study was only possible because of community led initiative of uploading obituary notifications to Facebook. Citizen science approaches combined with social media etc can help bridge the data gap.
Alternatively operations such as collating gravedigger burials to create new mortality data sources can help increase coverage of mortality statistics, e.g. in Addis Ababa reuters.com/article/us-hea…
And the Yemen study linked above is such a cool use of satellite imagery to estimate changes in burial patterns and is something that could easily be scaled and automated. Investing in these remote sensing approaches needs to happen to close the info gap. medrxiv.org/content/10.110…

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More from @ojwatson92

15 Sep 20
Our report investigating the under-reporting of COVID-19 deaths in Damascus, Syria was released this morning. This analysis has changed how I view the extent to which COVID-19 has potentially spread unobserved in many parts of the world. 1/n
Firstly, 2 main takeaways:

1. Best estimate is that 1 in 80 deaths due to COVID-19 have been reported as of 2nd September, suggesting that as many as 4,380 deaths may have been missed.
2. Epidemic in Damascus significantly more advanced than reported deaths would suggest 2/n
But how do we arrive at these estimates, in a setting that has been ravaged by war for nearly a decade leading to both weakened surveillance and health systems?

We start with excess mortality data. 3/n
Read 26 tweets
22 Mar 20
In light of @MRC_Outbreak report on US and UK #COVIDー19 epidemics, better tools for containment are needed to prevent additional waves. As @trvrb and others note, a technological solution should be developed. Singapore govt has just launched the Trace Together app. 1/n
tracetogether.gov.sg is a phone app for contact tracing, which will speed up how quickly the govt can identify potential transmission events and alert potentially infected individuals. 2/n
Trace together uses bluetooth to detect when users have spent more than 30 minutes within 2m of each other, constituting a significant contact event. User ids and contacts are encrypted stored on user's phone and only shared if user is identified as contacting a known case. 3/n
Read 11 tweets

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