Table 1.

A summary of the potential merits, criticisms, counter-arguments, and possible solutions associated with the WWW-BE as a hypothesis and decision-support tool in low-income countries.

Merits and opportunities	Potential criticisms and limitations	Counter-arguments and potential solutions
(1) WWW-BE builds on and extends W-BE, making WWW-BE potentially more ideal for low-income settings.	(1) Lack of global prior art and validation may lead to scepticism by the public, funders, and decision- and policy-makers.	This is a cross-cutting limitation, because no prior art and validation evidence exist in LICs even for W-BE. Research is required to validate, pilot test, and apply WWW-BE to develop the scientific evidence base to build confidence in the tool.
(2) WWW-BE modularity imparts potential flexibility and adaptability to diverse settings on a case-by-case basis.	(2) Heterogeneity, sampling difficulties, and low persistence of SARS-CoV-2 on solid waste may constrain the use of solid waste in epidemiology.	Solid media such as wastewater sludge has been sampled and used in epidemiology. SARS-CoV-2 and its proxies persist on solid materials. Sampling and sample preparation methods need to be developed and validated for solid waste.
(3) WWW-BE could serve a dual function to estimate the burden and potential transmission of COVID-19 in a spatial domain.	(3) Biosafety and human health risks associated with sampling, processing and disposal of WWW-BE media.	This is cross-cutting, and relevant to both WWW-BE and W-BE. Accredited laboratories with skilled personnel and high biosafety protocols are needed in LICs.
(4) Similar to W-BE, WWW-BE aggregates data, thus putatively requires less samples, time, and resources than conventional diagnostic individual testing.	(4) WWW-BE poses significant logistical and cost constraints in dispersed communities.	W-BE and diagnostic testing also face significant challenges in such settings. WWW-BE can be adapted to fill the gap by targeting on-site sanitation facilities. Mobile testing units, and rapid low-cost sensors need to be developed to support WWW-BE.
(5) WWW-BE could account for asymptomatic, oligosymptomatic and presymptomatic infected people, and those who may undergo self-isolation or quarantine without clinical testing.	(5) Bioethics and socio-cultural intrusion associated with sampling of WWW-BE media, and dissemination of results.	Similar to W-BE, WWW-BE is less intrusive than individual testing. WWW-BE outputs should presented as aggregated or clustered data rather than for individual households. Similar to other human health- related research, approvals and consent are required for WWW-BE.
(6) As a hypothesis and decision-support tool, WWW-BE has a potential to be extended beyond COVID-19 to other human infections in LICs such as cholera and typhoid.	(6) Lack of data, and validated tools for back-and forward-calculations to support WWW-BE.	Current W-BE tools, and those based on artificial intelligence and big data analytics can also be adapted, developed and validated through a comprehensive WWW-BE research programme entailing the acquisition of relevant data.
(7) WWW-BE could change the environmental surveillance paradigm in LICs, and presents translational research opportunities to pilot test, validate, and apply the hypothesis and decision-support tool.	(7) WWW-BE based COVID-19 estimates may entail high uncertainties due to sampling, analytical, and calculation errors.	This is cross-cutting, because uncertainity is also high for W-BE. This calls for further research to refine the analytical tools and address this potential limitation for both WWW-BE and W-BE.