What should exist for science and technology in the Arab world, but doesn't?
The first warning of the next pandemic may not come from a crowded emergency room or a hospital report. It may appear as a faint genetic trace in wastewater beneath a pilgrimage corridor, a refugee settlement or an informal neighbourhood that no clinical reporting system sees. During COVID-19, wastewater surveillance proved that it could detect rising virus levels days before hospitals reported a surge in cases. Yet in most of the Arab world, there is still no system designed to catch these early signals.
This is not a funding problem. It is a technical R&D problem with five layers: sampling representativeness in fragmented sewer networks, RNA preservation under extreme heat, signal normalization against irregular flows, variant detection from mixed environmental samples and decision thresholds that link noisy molecular data to action. No existing system solves all five under regional conditions. Building one is the missing scientific infrastructure.
The Core Bottleneck
Standard wastewater surveillance systems were designed around assumptions that hold in high-income countries: treatment plants that receive sewage from most of the population, reliable cold-chain transport, established sequencing labs and public health agencies with the capacity to act quickly on molecular signals. Most Arab cities break every one of these assumptions.
In cities like Amman or Cairo, large populations rely on septic tanks or informal drainage outside the central sewer network. A treatment plant at the city's edge may cover wealthy formal neighbourhoods while missing the districts most vulnerable to outbreaks producing data that is scientifically credible and epidemiologically blind.
Heat further challenges the assumptions behind standard wastewater surveillance. Under high-temperature conditions, viral RNA in untreated wastewater degrades far more rapidly than it does in cold environments. This is especially important in the Gulf, where a sample transported across a city during summer without refrigeration may experience substantial signal loss before it reaches the laboratory. As a result, standard protocols may underestimate viral presence or fail to detect it altogether.
A promising approach is immediate field-based RNA extraction using lightweight, electricity-free preparation methods. Such methods could preserve genetic material without relying on a cold chain, making them more suitable for hot and resource-variable settings. However, these techniques still require validation under the specific chemical composition, organic load, and environmental conditions of wastewater in Arab urban systems. Establishing that reliability is a central part of the required research.
Sequencing adds a third layer. Tools like Freyja estimate variant frequencies from mixed wastewater samples by matching mutation patterns against barcodes in the UShER global phylogenetic tree but that database is built predominantly from North American and European sequences. Locally circulating sublineages in the Eastern Mediterranean or Gulf that never achieved global variant-of-concern status are absent from the reference set. When Freyja encounters such a lineage, it collapses it to a generic ancestral branch, erasing the signal that the system most needs to detect. Applying these tools without regional recalibration introduces a directional blind spot precisely where novel variants are most likely to emerge.
The R&D Agenda
I write this not as an outside observer. I was part of a study that confirmed the detection of SARS-CoV-2 in untreated municipal and aircraft wastewater in Dubai, UAE. This experience showed me that wastewater can provide valuable public health information before traditional clinical systems detect a problem. Aircraft wastewater from international flights demonstrated how airports can serve as early warning points for imported infections. Municipal wastewater also showed how different parts of the city can produce different signals depending on sewer connectivity. Together, these findings highlighted the value of using several sampling locations rather than depending only on treatment plants.
This work strengthened my belief that Dubai is an ideal place to develop a regional wastewater surveillance system. The city combines one of the world’s busiest airports, a modern sewer network, complex catchment areas, extreme summer heat, and institutions capable of supporting public health innovation. These conditions make Dubai not only a challenging environment, but also a powerful testing ground for a system designed for the wider Arab world. A successful pilot could begin with a focused multidisciplinary team of five people: an environmental engineer, a molecular biologist, a genomic epidemiologist, a public health partner, and a data scientist. Together, this team would bring the expertise needed to collect samples, analyze genetic signals, interpret the results, and turn wastewater data into practical public health action.
The first workstream is the development of a sampling typology. Different sampling sites provide different types of information, and each has its own limitations. A treatment plant inlet can show broad city-level trends, but it may miss informal districts that are not connected to the central sewer system. A hospital outflow can help monitor antimicrobial resistance and healthcare-associated pathogens. A neighborhood manhole can capture local community transmission that may not appear at the treatment plant. An airport catchment can detect imported pathogens before they are identified through clinical testing. For this reason, an effective wastewater surveillance system should combine multiple sampling points rather than rely only on the most convenient location.
The second workstream is signal normalization. An increase in pathogen concentration does not always mean that disease transmission is rising. It may also result from changes in wastewater flow, such as reduced water use, water scarcity, or dilution after rainfall. To make the data interpretable, the team would measure human faecal markers, such as PMMoV and crAssphage, together with flow-rate data. These measurements would provide a population-adjusted reference point, allowing signals to be compared more accurately across the irregular wastewater flows common in Arab urban infrastructure.
The third workstream is heat-stable field preservation. The team would compare electricity-free field extraction, passive Moore swab sampling, and grab sampling under realistic Gulf temperature conditions. Each protocol would include a process control to detect PCR inhibition and sample failure. If the control fails, the sample would be treated as uninterpretable rather than being mistaken for a true negative result. This step is essential because wastewater often contains substances that can interfere with molecular testing.
The fourth workstream is a tiered testing model. Routine qPCR testing would focus on a narrow and practical panel, including respiratory viruses, enteric viruses, cholera markers where relevant, and priority antimicrobial resistance genes. These tests could be performed weekly at relatively low cost. When a signal increases, appears at a high-risk site, or conflicts with clinical data, deeper genomic analysis would be triggered. Regional genomic pipelines would then be adjusted to include locally circulating strains, improving the ability to identify variants present in mixed wastewater samples. Broader metagenomic testing would be reserved for unexplained signals or high-risk mobility sites.
The fifth workstream is a decision-threshold framework. Wastewater data must be linked to clear public health actions. A baseline detection may require continued monitoring. A sustained rise above the normalized baseline may trigger comparison with clinical indicators. Detection of a new variant cluster may lead to targeted sequencing. A conflict between wastewater signals and clinical reports may require field investigation. These thresholds should be tested over time against hospital admissions, pharmacy trends, and other public health data to ensure that the system produces reliable and actionable warnings.
Why It Must Be Arab-Specific
The mobility patterns of the Arab world are not a complication to manage but they are a design input. The Hajj and Umrah move three to four million people from over 180 countries through the Hejaz annually, then disperse them home within weeks. Gulf labor routes carry millions between South Asia, East Africa and the Peninsula. The Arab world hosts a disproportionate share of the world’s displaced populations. A surveillance system not deliberately sited at airports, border crossings, labor-hub municipalities and pilgrimage corridors is not a surveillance system for this region. It is a system for a different region, imported and relabelled.
The trust dimension is equally non-negotiable. Wastewater surveillance does not identify individuals, which is its epidemiological strength but results can be misused to stigmatize neighbourhoods, target refugee communities or feed immigration enforcement. Any system built here must separate public-health surveillance from policing structurally, not just rhetorically, with data published at the district level under a transparent public-health mandate. This is a prerequisite for the community cooperation without which sampling becomes impossible and data becomes unrepresentative.
What a Successful Pilot Produces
After twelve months, a working pilot in one Arab city should yield six transferable outputs: a validated sampling map linking sites to actual catchment populations; a field preservation protocol with documented RNA recovery under regional temperature and transport conditions, including BCoV process-control performance data; a qPCR panel with known detection limits and per-sample cost; a regionally recalibrated Freyja pipeline with validated sensitivity for locally circulating lineages; a PMMoV and flow-normalized decision-threshold framework linked to clinical benchmarks; and a scale-up manual for other cities with different infrastructure profiles. A city that has done this work can train two others in a year.
The long-term form is a hub-and-spoke network: local teams collect samples and run qPCR while regional sequencing centres anchored at institutions such as Institut Pasteur de Tunis, KAUST or Dubai Genome Centre provide genomic analysis, quality control, shared variant databases and barcode updates as locally dominant lineages emerge. The network compares pathogen evolution across climate zones, infrastructure types and mobility corridors in a way no single country can achieve alone.
This is not a dashboard. It is a working early-warning system: Is a respiratory virus rising in informal settlements before hospitals see it? Is the rise a known strain or a lineage absent from current diagnostic targets? Are pilgrimage corridors or airport catchments showing variant signals clinical testing has not resolved? The work to answer these questions in Dubai is already underway. What began as a study detecting SARS-CoV-2 in untreated municipal and aircraft wastewater before clinical systems registered it is now the foundation for a city-wide multi-pathogen surveillance architecture, integrating multi-site sampling, flow normalization, heat-stable field protocols and regionally calibrated genomic pipelines — designed to predict disease emergence, not merely document it. The Arab world has the scientific talent. It needs the infrastructure to connect that talent to its actual problems: designed for its heat, its fragmented sewers, its mobility patterns and its blind spots in global genomic databases. Dubai is where it starts. The region is where it scales.