Tailored intelligence to detect unusual epidemic activity following the explosion at Vector, Russia

Abstract

We used open source data from the EpiWATCH observatory to monitor for early disease signals in Russia and surrounding countries following an explosion at a BSL 4 laboratory, Vector, in Siberia in September 2019. Upon news of the explosion at Vector on September 16th 2019, the EpiWATCH team added the Russian language and key words Russia, Siberia, Novosibirsk, and Koltsovo to the Standard Operating Procedures, in addition to the usual epidemic-specific keywords used in EpiWATCH. We also searched for outbreak reports in countries bordering Siberia, including Mongolia, Kazakhstan and China. Given local spread of an epidemic could manifest in these countries, we included searching in Chinese, Mongolian and Kazakh. We added "Ukraine" as a key word, given current conflict between Russia and Ukraine. Data collection began in September 2019, one week after the explosion, with this considered the baseline. We demonstrate a method for rapid epidemic intelligence following an incident of concern, the explosion at Vector. There were some unexplained outbreaks in Russia in the three months following the explosion. No unexplained outbreaks were detected in countries bordering Russia, nor in Ukraine in the three months following the explosion. We detected an accidental release of brucella from a laboratory in China in early December 2019 and two reports of severe pneumonia prior to official reports, which could have been early COVID-19 cases. Best practice in preparedness should include surveillance for disease events in the months following an event of concern at local, national and global levels. In the absence of official surveillance data, open source intelligence may be the only available means of detecting outbreaks and enabling early response and mitigation for the rest of the world. EpiWATCH was able to identify reports of Russian outbreaks in the weeks and months following the Vector explosion, which allowed monitoring of outbreaks of concern without a known cause.

Respiratory illness of unknown cause as an early signal of the COVID-19 pandemic

“…In Russia and the US, respiratory illnesses had reportedly increased earlier than expected for the season, with more severe disease, and unusually high numbers. Several factors could explain these cases, such as seasonal trends in common respiratory illnesses [42], lack of laboratory testing or reporting of diagnostic results, or the gas explosion on 16-Sep-2019 at the State Research Centre of Virology and Biotechnology (Vector Institute) in Siberia, which sparked concerns of accidental release of infectious pathogens [43]. There were reports of several respiratory illness cases that could not be diagnosed despite laboratory testing, including one report from Kemerovo Oblast in Siberia, dated six weeks after the Vector lab explosion [32].…”

Syndromic Surveillance 2.0: Emerging Global Surveillance Strategies for Infectious Disease Epidemics

“…Although, for scoping purposes, we focus primarily on the role of natural biologic threats as a source of disease emergence in this report, it is worth mentioning that deliberate or accidental biologic threats also exist (Office of the Assistant Secretary for Preparedness and Response, 2022). Examples of safety risks and accidental pathogen emergence suggest that there might be a benefit to monitoring these potential sources of disease outbreaks as well (MacIntyre et al, 2020;Noyce and Evans, 2018). 3 Furthermore, the threat of pathogen emergence from laboratory sources might increase over time given an increase in the quantity of laboratories working with high-risk pathogens (defined as biosafety level 3 and level 4) around the world (Peters, 2018).…”