Feasibility of wastewater-based detection of emergent pandemics through a global network of airports

Abstract

Wastewater-based surveillance has been put into practice during the pandemic. Persistence of SARS-CoV-2 in faeces of infected individuals, and high volume of passengers travelling by air, make it possible to detect virus from aircraft wastewater, lending itself to the potential identification of a novel pathogen prior to clinical diagnosis. In this study, we estimated the likelihood of detecting the virus through aircraft wastewater from the probabilities of air travel, viral shedding, defecation, testing sensitivity, and sampling. We considered various hypothetical scenarios, with diverse sampling proportions of inbound flights, surveillance airports, and sources of outbreaks. Our calculations showed that the probability of detecting SARS-CoV-2 would increase exponentially against time in the early phase of the pandemic, and would be much higher if the 20 major airports in Asia, Europe, and North America cooperated to perform aircraft wastewater surveillance. We also found other contributors to early detection, including high sampling proportion of inbound flight at destination airports, small population size of the epicentre relative to the travel volume, and large volume of outbound travelers to major airports around the globe. We concluded that routine aircraft wastewater monitoring could be a feasible approach for early identification and tracking of an emerging pathogen with high faecal shedding rates, particularly when implemented through a global surveillance network of major airports.

Fig 1. Model schematic.

Graphical derivation of the final detection probability from the probabilities of air travel, viral shedding, defecation, fecal testing positivity, and sampling.

Fig 2. World map of the airports studied.

Location of Wuhan (WUH), hypothetical epicentres (Madrid [Madrid], Miami [MIA], Mombasa [MBA], and Mumbai [BOM]), and a network of 20 major airports around the globe. The lines represent (postulated) direct flights from Wuhan in 2019, and the line widths are proportional to the (estimated) travel volume in 2019 [20].

Fig 3. Validation and projection from the case model.

(a) Fitted and observed number of new cases from 1 December 2019 to 8 January 2020, assuming only severe infections (20%) were detected; (b) fitted and observed number of new cases from 15 January to 8 February 2020, assuming a constant ascertainment rate; (c) predicted cumulative number of infections using our model, from 1 December 2019 to 22 January 2020, before Wuhan was locked down.

Fig 4. Cumulative probability of detecting SARS-CoV-2 against time in airports operating independently.

The probability of SARS-CoV-2 having been detected by day t when the aircraft wastewater was sampled with a probability of 100%, 50%, 20%, or 10% in any one of the 14 airports with direct flights from Wuhan between 9 December 2019 and 22 January 2020.

Fig 5. Detection probability against time for different epicentres.

The probability of the virus having been detected by day t (column 1) or first detected on day t (column 2) under four scenarios with diverse sampling probabilities (100%, 50%, 20%, 10%) for inbound flights, assuming different epicentres—Wuhan, Madrid, Miami, Mombasa, and Mumbai—and routine aircraft wastewater surveillance at all the 20 airports investigated.