David Aaron Larsen

Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021–April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in- network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs. Significance Statement: Municipal wastewater samples can be tested for infectious diseases circulating in sewered populations, but most surveillance systems exclude rural communities lacking sewer connections. Using clinical COVID-19 data from New York State, we demonstrate that routine human movement between in-network and off-network areas causes wastewater signals to reflect disease dynamics across sewer boundaries. In-network and off-network epidemic trends were highly correlated across both counties and mobility-defined communities, and testing wastewater can effectively surveil infectious diseases among populations beyond the limits of wastewater infrastructure. However, representativeness weakens in smaller communities, and 42% of mobility-defined communities have no wastewater infrastructure. Expanding wastewater surveillance to rural facilities should be treated as a surveillance-equity priority to ensure equitable early-warning capabilities for all communities.

Predicting epidemic surges is challenging and often relies on prior seasons, outbreaks in other regions, and advanced modeling of surveillance data. Using foundational principles of disease growth and spread, including trend analysis and overdispersion, we developed a surge detection algorithm for emerging pathogens that requires no historical baselines or seasonal assumptions. We used it to evaluate temporal variability (coefficient of variation, CV) and spatial clustering (global Moran's I) as early warning indicators across three parallel SARS-CoV-2 surveillance streams: wastewater, clinical cases, and hospitalizations. All metrics showed consistent variability patterns across epidemic phases that predicted surge onset and decline approximately one month in advance. For weekly pre-surge detection, sensitivity and positive predictive value reached 75% and 54%. CV additionally signaled surge termination, with up to 70% sensitivity and 59% positive predictive value. When evaluated per surge, by requiring only a single correct signal within each phase, CV detected 86 to 98% of onsets and 73 to 85% of terminations. These signatures held across surveillance streams and geographic scales, suggesting they reflect system-level transmission dynamics rather than stream-specific artifacts, consistent with overdispersed transmission producing high variability before and after peak. Requiring only basic quantitative methods, our framework is implementable by practitioners without specialized training in dynamical systems.

Sequencing genetic material from community wastewater facilitates the study of virus diversity. Diversity can be estimated using the variation in nucleotides and number of variants identified, increasing the information obtained from one wastewater sample. Using 12,290 wastewater sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we found that virus diversity is a strong indicator of disease transmission, with a significant correlation between average weekly diversity and average weekly new COVID-19 infections. Although the concentration of viruses is the common measure of disease transmission from wastewater, we found that diversity is a better indicator, as it is unhampered by the noise inherent in the wastewater. We show that multiple measures of diversity yield similar results, which suggests that genetic diversity could be useful for increasing the utility of wastewater data.

Background: Wastewater–based epidemiology (WBE) has the potential to produce reliable, efficient, and non-invasive measures of current psychoactive drug use. The aim of this study was to assess the feasibility and validity of using WBE to estimate current cocaine use among university students at a residential campus. Methods: We analyzed wastewater samples from four locations at a residential university campus during spring semester of 2021, testing for cocaine metabolites in addition to control comparison substances (acetaminophen and caffeine). We simultaneously administered a confidential self-report survey of recent substance use behaviors to a randomized sample of undergraduate students at this university. Results: Self-reported survey estimates of cocaine use and point estimates of cocaine use derived from wastewater-based epidemiology are similar, but the survey is imprecise with a wide CI, and agreement is sensitive to key WBE assumptions; thus, results are consistent but not conclusive. The self-report survey results indicated 0.13% of respondents were regular cocaine users, which is equivalent to the estimate of 0.12% of students using cocaine as measured through WBE. This prevalence is also in line with the 0.14% National American College Health Association (NACHA) survey during the same semester. Conclusions: WBE shows promise as a complementary approach for estimating current cocaine use among students on a residential campus; with current data the WBE point estimate is similar to the survey point estimate, but uncertainty in both measures (especially the survey) requires further research.

Indoor residual spraying (IRS) is a vector control tool recommended by the WHO in areas of high malaria burden. Effective IRS implementation is complicated when up-to-date and accurate counts of structures eligible for IRS are unavailable; resultingly, programmatic spray coverage is typically calculated as the proportion of found structures that are sprayed. From 2016 – 2020 in Zambia, an open-source tool termed “Reveal,” was used to support digital mapping, microplanning, campaign monitoring and evaluation of IRS. Satellite imagery was used to enumerate structures and identify “spray areas,” clusters of structures for operational planning. Spray areas were visualized in the Reveal tool web-based planning module where campaign planners selected which would be sprayed and determined the resources required. Field teams used the Reveal tool mobile application to navigate and to record spray data against each structure. True coverage was calculated as the proportion of enumerated structures that were sprayed. Reveal was implemented in 21 districts across five years and coverage is reported for each district and year. Logistic regression models explored whether structures were more or less likely to be found and sprayed depending on a given calendar year’s targeting strategy, partner support level, and the year of Reveal implementation in a given district (first, second, third, or fourth). District-level programmatic IRS coverages overestimated the true adjusted coverages by an average 31.5 percentage points (range 2.8 - 69.4). The odds of finding and spraying structures increased with year of implementation; in the fourth year of implementation in a district, the odds of a household being sprayed and found were two times higher than in the first year of implementation. Digital tools improve structure and population estimates for planning and deployments in IRS campaigns, which may lead to more accurate coverage measurements and increased coverage over time.

Dengue, Zika, and chikungunya, all transmitted by Aedes aegypti mosquitoes, present a significant and growing global health challenge. Contact-based insecticide such as pyrethroids, organophosphates, and organochlorines, are a core component of strategies to control Ae. aegypti . However, reliance on these chemical insecticides alone presents long-term challenges, particularly around increasing insecticide resistance. There are relatively few novel tools available that target adult mosquitoes through alternative mechanisms. Innovative, complementary approaches that can enhance the effectiveness and sustainability of existing mosquito control programs are urgently needed. Newly explored vector management tools are attractive toxic sugar baits (ATSBs), targeting the sugar-feeding behavior of both male and female mosquitoes, and allow for an ingested insecticide. Dried Attractive Bait Stations (DABS), a novel variant of ATSBs, have shown promising results for indoor Ae. aegypti control. We conducted cage and experimental house trials of DABS on laboratory-reared Ae. aegypti mosquitoes in Ponce, Puerto Rico. In cage trials, both male and female Ae. Aegypti that were exposed to DABS for 48 hours experienced near complete mortality, while control groups showed universal survival. All tested concentrations (1%, 2%, and 4% boric acid compounds) significantly reduced survival compared to controls ( p < 0.001), with no significant differences between concentrations ( p = 0.50). Water availability reduced DABS efficacy, lowering mortality by 47% in females ( p < 0.001) and 32% in males ( p < 0.001). In experimental house trials, DABS reduced mosquito survival by ∼75% ( p < 0.001), with deployment of four DABS devices per room suggesting the greatest reduction in mosquito survival ( p = 0.06–0.10). Optimal performance was observed at placing DABS 0.75 m above the floor ( p < 0.001) and results suggest that medium-sized DABS may be more effective than larger ( p = 0.09). Natural light increased mosquito survival ( p = 0.028), but its interaction with DABS treatment was not significant ( p = 0.322) and room-to-room variability was minimal. A notable limitation was the interference of ants during household trials, which led to the removal of mosquito carcasses and potential data loss, highlighting the need to further investigate alternative sugar sources and DABS interaction with non-target organisms. Despite these challenges, the results support DABS as a promising, scalable Aedes aegypti control tool. Future research should confirm effectiveness under varied field conditions, and assess the community acceptability for broader deployment.

Sequencing viruses found in community wastewater facilitates the study of diversity in circulating viruses at the population level. By analyzing 12,290 wastewater samples collected between January 2023 and April 2025 in New York State, USA from 196 sampling sites across 57 counties, we assessed the diversity of the SARS-CoV-2 genome and how it changed over time compared to changes in COVID-19 infections and hospitalizations. We calculated three measures of SARS-CoV-2 genome diversity across all samples: nucleotide diversity ( π ), Shannon diversity (H), and viral variant count. We found that diversity increased with a rise in COVID-19 incidence and hospitalizations for all three measures (with a Spearman ρ > 0.8, pρ = 0.92, pπ, ρ = 0.91, p ρ = 0.85 (p<0.001) with case incidence. Additionally, the genetic diversity of the spike protein predicted 90.1 percent of the variance of COVID-19 case incidence. Our results demonstrate the potential for viral diversity analysis from wastewater in predicting epidemiological outcomes.