Syndromic surveillance of population-level COVID-19 burden with cough monitoring in a hospital emergency waiting room.

Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital's electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value < 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Aggregated cough counts and other data, such as people density collected from our platform, can be utilized to predict COVID-19 patient visits related metrics in a hospital waiting room, and SHAP and Gini feature importance-based metrics showed cough count as the important feature for these prediction models. Furthermore, we have shown that predictions based on cough counting outperform models based on fever detection (e.g., temperatures over 39°C), which require more intrusive engagement with the population. Our findings highlight that incorporating cough-counting based signals into syndromic surveillance systems can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics.

Passive Monitoring of Crowd-Level Cough Counts in Waiting Areas produces Reliable Syndromic Indicator for Total COVID-19 Burden in a Hospital Emergency Clinic.

Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital's electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value < 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Our findings highlight the efficacy of aggregated cough count as a valuable syndromic indicator associated with the occurrence of COVID-19 cases. Incorporating this signal into syndromic surveillance systems for such diseases can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics.

Knowledge, attitudes, and practices regarding COVID-19 among university students and employees in Massachusetts, USA: A qualitative study.

OBJECTIVE: To explore the knowledge, attitudes, and practices regarding COVID-19 in university affiliates to inform future COVID-19 policies and practices. PARTICIPANTS: Undergraduate students, graduate students and university employees at a large public university. METHODS: Semi-structured focus groups and interviews were conducted between December 2020 and January 2021. Data were analyzed via inductive thematic analysis. RESULTS: Analysis of data from the 36 participants generated five themes: COVID-19 knowledge, stress and coping, trust, decision-making, and institutional feedback. Misunderstanding of COVID-19 preventive behaviors was common, which appeared to compound high levels of stress and presented an educational opportunity. University investment in an asymptomatic testing program was reported to increase perceived safety. CONCLUSIONS: Participants' experiences with a large university's COVID-19 response suggest a desire for consistent and transparent communication and an opportunity for institutions to examine the effectiveness of their communication strategies, public health protocols, and mechanisms for assessing and mitigating stress.

Optimizing the implementation of a participant-collected, mail-based SARS-CoV-2 serological survey in university-affiliated populations: lessons learned and practical guidance.

The rapid spread of SARS-CoV-2 is largely driven by pre-symptomatic or mildly symptomatic individuals transmitting the virus. Serological tests to identify antibodies against SARS-CoV-2 are important tools to characterize subclinical infection exposure.During the summer of 2020, a mail-based serological survey with self-collected dried blood spot (DBS) samples was implemented among university affiliates and their household members in Massachusetts, USA. Described are challenges faced and novel procedures used during the implementation of this study to assess the prevalence of SARS-CoV-2 antibodies amid the pandemic.Important challenges included user-friendly remote and contact-minimized participant recruitment, limited availability of some commodities and laboratory capacity, a potentially biased sample population, and policy changes impacting the distribution of clinical results to study participants. Methods and lessons learned to surmount these challenges are presented to inform design and implementation of similar sero-studies.This study design highlights the feasibility and acceptability of self-collected bio-samples and has broad applicability for other serological surveys for a range of pathogens. Key lessons relate to DBS sampling, supply requirements, the logistics of packing and shipping packages, data linkages to enrolled household members, and the utility of having an on-call nurse available for participant concerns during sample collection. Future research might consider additional recruitment techniques such as conducting studies during academic semesters when recruiting in a university setting, partnerships with supply and shipping specialists, and using a stratified sampling approach to minimize potential biases in recruitment.

Quantifying the Relationship between SARS-CoV-2 Wastewater Concentrations and Building-Level COVID-19 Prevalence at an Isolation Residence: A Passive Sampling Approach.

SARS-CoV-2 RNA loads can be detected in the excreta of individuals with COVID-19 and have demonstrated positive correlations with clinical infection trends. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor community-level prevalence of infections. The majority of wastewater specimens are gathered as either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and can be challenging to maintain in cold weather, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Passive sampling can provide an affordable, practical, and scalable sampling system while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from 1 February 2021-21 May 2021. Samples (n = 64) were collected 3-5 times weekly and remained within the sewer for a median duration of 24 h. SARS-CoV-2 RNA was quantified using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform building-level public health responses.

Quantifying the relationship between SARS-CoV-2 wastewater concentrations and building-level COVID-19 prevalence at an isolation residence using a passive sampling approach.

SARS-CoV-2 RNA can be detected in the excreta of individuals with COVID-19 and has demonstrated a positive correlation with various clinical parameters. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor the community-level prevalence of infections. Over 270 higher education campuses monitor wastewater for SARS-CoV-2, with most gathering either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and challenging to manage with seasonal variability, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Prior studies have demonstrated encouraging results utilizing passive sampling swabs. Such methods can offer affordable, practical, and scalable alternatives to traditional methods while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from February 1, 2021 â€" May 21, 2021. Samples were collected several times weekly and remained within the sewer for a minimum of 24 hours (n = 64). SARS-CoV-2 RNA was quantified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) targeting the viral N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform public health responses in a range of settings. Highlights: Daily SARS-CoV-2 RNA loads in building-level wastewater were positively associated with the total number of COVID-19 positive individuals in the residenceThe variation in individual fecal shedding rates of SARS-CoV-2 extended four orders of magnitudeWastewater sample replicates were highly correlated using distinct processing pipelines in two independent laboratoriesWhile the isolation residence was occupied, SARS-CoV-2 RNA was detected in all passive samples.

Considerations for Meeting Students' Mental Health Needs at a U.S. University During the COVID-19 Pandemic: A Qualitative Study.

Objective: To better understand the potential ongoing effects of the COVID-19 pandemic on U.S. university students' mental health and to generate hypotheses as to how universities may best meet students' mental health needs. Participants: Students at a large public university in the United States. Methods: Students were invited via email to participate in either interviews or focus groups regarding their COVID-19 pandemic experiences, including mental health impacts. Recruitment took place in two waves. Sessions were led by student members of the research team and took place via video conference between December 2020 and June 2021. Interviews were audio-recorded and transcribed via Zoom and manually edited and de-identified by the research team. Interview data were analyzed deductively and inductively using a modified grounded theory approach. Results: A total of 40 undergraduate and graduate students took part in the study. Major themes included: (1) Overall impact of the pandemic on mental health; (2) Sources of pandemic stress/mental health impacts; (3) Subsequent coping strategies; and (4) Suggestions for improving university support for student mental health. Subthemes were identified within each major theme. Students reported substantial anxiety and other mental health impacts and felt improvements in communication and access to mental health resources could better support students. Conclusions: This study provides context for the ways in which the COVID-19 pandemic may be continuing to impact mental health in a north-American university setting and identifies suggestions for potential interventions that future studies may test for effectiveness.

Civilian-military malaria outbreak response in Thailand: an example of multi-stakeholder engagement for malaria elimination.

BACKGROUND: In April 2017, the Thai Ministry of Public Health (MoPH) was alerted to a potential malaria outbreak among civilians and military personnel in Sisaket Province, a highly forested area bordering Cambodia. The objective of this study was to present findings from the joint civilian-military outbreak response. METHODS: A mixed-methods approach was used to assess risk factors among cases reported during the 2017 Sisaket malaria outbreak. Routine malaria surveillance data from January 2013 to March 2018 obtained from public and military medical reporting systems and key informant interviews (KIIs) (n = 72) were used to develop hypotheses about potential factors contributing to the outbreak. Joint civilian-military response activities included entomological surveys, mass screen and treat (MSAT) and vector control campaigns, and scale-up of the "1-3-7" reactive case detection approach among civilians alongside a pilot "1-3-7" study conducted by the Royal Thai Army (RTA). RESULTS: Between May-July 2017, the monthly number of MoPH-reported cases surpassed the epidemic threshold. Outbreak cases detected through the MoPH mainly consisted of Thai males (87%), working as rubber tappers (62%) or military/border police (15%), and Plasmodium vivax infections (73%). Compared to cases from the previous year (May-July 2016), outbreak cases were more likely to be rubber tappers (OR = 14.89 [95% CI: 5.79-38.29]; p < 0.001) and infected with P. vivax (OR=2.32 [1.27-4.22]; p = 0.006). Themes from KIIs were congruent with findings from routine surveillance data. Though limited risk factor information was available from military cases, findings from RTA's "1-3-7" study indicated transmission was likely occurring outside military bases. Data from entomological surveys and MSAT campaigns support this hypothesis, as vectors were mostly exophagic and parasite prevalence from MSAT campaigns was very low (range: 0-0.7% by PCR/microscopy). CONCLUSIONS: In 2017, an outbreak of mainly P. vivax occurred in Sisaket Province, affecting mainly military and rubber tappers. Vector control use was limited to the home/military barracks, indicating that additional interventions were needed during high-risk forest travel periods. Importantly, this outbreak catalyzed joint civilian-military collaborations and integration of the RTA into the national malaria elimination strategy (NMES). The Sisaket outbreak response serves as an example of how civilian and military public health systems can collaborate to advance national malaria elimination goals in Southeast Asia and beyond.

Prevalence of glucose-6-phosphate dehydrogenase deficiency (G6PDd), CareStart qualitative rapid diagnostic test performance, and genetic variants in two malaria-endemic areas in Sudan.

Glucose-6-phosphate dehydrogenase deficiency (G6PDd) is the most common enzymopathy globally, and deficient individuals may experience severe hemolysis following treatment with 8-aminoquinolines. With increasing evidence of Plasmodium vivax infections throughout sub-Saharan Africa, there is a pressing need for population-level data at on the prevalence of G6PDd. Such evidence-based data will guide the expansion of primaquine and potentially tafenoquine for radical cure of P. vivax infections. This study aimed to quantify G6PDd prevalence in two geographically distinct areas in Sudan, and evaluating the performance of a qualitative CareStart rapid diagnostic test as a point-of-care test. Blood samples were analyzed from 491 unrelated healthy persons in two malaria-endemic sites in eastern and central Sudan. A pre-structured questionnaire was used which included demographic data, risk factors and treatment history. G6PD levels were measured using spectrophotometry (SPINREACT) and first-generation qualitative CareStart rapid tests. G6PD variants (202 G>A; 376 A>G) were determined by PCR/RFLP, with a subset confirmed by Sanger sequencing. The prevalence of G6PDd by spectrophotometry was 5.5% (27/491; at 30% of adjusted male median, AMM); 27.3% (134/491; at 70% of AMM); and 13.1% (64/490) by qualitative CareStart rapid diagnostic test. The first-generation CareStart rapid diagnostic test had an overall sensitivity of 81.5% (95%CI: 61.9 to 93.7) and negative predictive value of 98.8% (97.3 to 99.6). All persons genotyped across both study sites were wild type for the G6PD G202 variant. For G6PD A376G all participants in New Halfa had wild type AA (100%), while in Khartoum the AA polymorphism was found in 90.7%; AG in 2.5%; and GG in 6.8%. Phenotypic G6PD B was detected in 100% of tested participants in New Halfa while in Khartoum, the phenotypes observed were B (96.2%), A (2.8%), and AB (1%). The African A- phenotype was not detected in this study population. Overall, G6PDd prevalence in Sudan is low-to-moderate but highly heterogeneous. Point-of-care testing with the qualitative CareStart rapid diagnostic test demonstrated moderate performance with moderate sensitivity and specificity but high negative predicative value. The two sites harbored primarily the African B phenotype. A country-wide survey is recommended to understand GP6PD deficiencies more comprehensively in Sudan.

Serological surveys to estimate cumulative incidence of SARS-CoV-2 infection in adults (Sero-MAss study), Massachusetts, July-August 2020: a mail-based cross-sectional study.

OBJECTIVES: To estimate the seroprevalence of anti-SARS-CoV-2 IgG and IgM among Massachusetts residents and to better understand asymptomatic SARS-CoV-2 transmission during the summer of 2020. DESIGN: Mail-based cross-sectional survey. SETTING: Massachusetts, USA. PARTICIPANTS: Primary sampling group: sample of undergraduate students at the University of Massachusetts, Amherst (n=548) and a member of their household (n=231).Secondary sampling group: sample of graduate students, faculty, librarians and staff (n=214) and one member of their household (n=78). All participants were residents of Massachusetts without prior COVID-19 diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: Prevalence of SARS-CoV-2 seropositivity. Association of seroprevalence with variables including age, gender, race, geographic region, occupation and symptoms. RESULTS: Approximately 27 000 persons were invited via email to assess eligibility. 1001 households were mailed dried blood spot sample kits, 762 returned blood samples for analysis. In the primary sample group, 36 individuals (4.6%) had IgG antibodies detected for an estimated weighted prevalence in this population of 5.3% (95% CI: 3.5 to 8.0). In the secondary sampling group, 10 participants (3.4%) had IgG antibodies detected for an estimated adjusted prevalence of 4.0% (95% CI: 2.2 to 7.4). No samples were IgM positive. No association was found in either group between seropositivity and self-reported work duties or customer-facing hours. In the primary sampling group, self-reported febrile illness since February 2020, male sex and minority race (Black or American Indian/Alaskan Native) were associated with seropositivity. No factors except geographic regions within the state were associated with evidence of prior SARS-CoV-2 infection in the secondary sampling group. CONCLUSIONS: This study fills a critical gap in estimating the levels of subclinical and asymptomatic infection. Estimates can be used to calibrate models estimating levels of population immunity over time, and these data are critical for informing public health interventions and policy.

Population size estimation of seasonal forest-going populations in southern Lao PDR.

Forest-going populations are key to malaria transmission in the Greater Mekong Sub-region (GMS) and are therefore targeted for elimination efforts. Estimating the size of this population is essential for programs to assess, track and achieve their elimination goals. Leveraging data from three cross-sectional household surveys and one survey among forest-goers, the size of this high-risk population in a southern province of Lao PDR between December 2017 and November 2018 was estimated by two methods: population-based household surveys and capture-recapture. During the first month of the dry season, the first month of the rainy season, and the last month of the rainy season, respectively, 16.2% [14.7; 17.7], 9.3% [7.2; 11.3], and 5.3% [4.4; 6.1] of the adult population were estimated to have engaged in forest-going activities. The capture-recapture method estimated a total population size of 18,426 [16,529; 20,669] forest-goers, meaning 61.0% [54.2; 67.9] of the adult population had engaged in forest-going activities over the 12-month study period. This study demonstrates two methods for population size estimation to inform malaria research and programming. The seasonality and turnover within this forest-going population provide unique opportunities and challenges for control programs across the GMS as they work towards malaria elimination.

Ivermectin Treatment for Cattle Reduced the Survival of Two Malaria Vectors, Anopheles dirus and Anopheles epiroticus, Under Laboratory Conditions in Central Vietnam.

Ivermectin is a low-cost and nontoxic mosquitocide that may have a role in malaria elimination. However, the extent to which this drug impacts the mortality of Anopheles dirus and Anopheles epiroticus, two important malaria vectors in Southeast Asia, is unknown. This study compared and quantified anopheline mortality after feeding on ivermectin-treated cattle and control cattle in Vietnam. Local anopheline colonies fed on cattle 1 to 3, 6 to 8, 13 to 15, 20 to 22, and 28 to 30 days after injection (DAI) with ivermectin (intervention) or saline (control). An. dirus that fed on ivermectin-treated cattle had higher mortality rates than controls for up to 20 DAI (P < 0.05); An. epiroticus that fed on ivermectin-treated cattle had consistently higher mortality rates than controls for up to 8 DAI (P < 0.05). Feeding on ivermectin-treated cattle increased the mortality rate of these vector species for biologically relevant time periods. Therefore, ivermectin has the potential to become an important tool for integrated vector management.

Spatio-temporal associations between deforestation and malaria incidence in Lao PDR.

As countries in the Greater Mekong Sub-region (GMS) increasingly focus their malaria control and elimination efforts on reducing forest-related transmission, greater understanding of the relationship between deforestation and malaria incidence will be essential for programs to assess and meet their 2030 elimination goals. Leveraging village-level health facility surveillance data and forest cover data in a spatio-temporal modeling framework, we found evidence that deforestation is associated with short-term increases, but long-term decreases confirmed malaria case incidence in Lao People's Democratic Republic (Lao PDR). We identified strong associations with deforestation measured within 30 km of villages but not with deforestation in the near (10 km) and immediate (1 km) vicinity. Results appear driven by deforestation in densely forested areas and were more pronounced for infections with Plasmodium falciparum (P. falciparum) than for Plasmodium vivax (P. vivax). These findings highlight the influence of forest activities on malaria transmission in the GMS.

Biting mosquitos spread the malaria parasite to humans. Along the Mekong River in Southeast Asia, spending time in the surrounding forest increases a person's risk of malaria. This has led to a debate about whether deforestation in this area, which is called the Greater Mekong Sub-region (GMS), will increase or decrease malaria transmission. The answer to the debate is not clear because some malaria-transmitting mosquitos thrive in heavily forested areas, in particular in the GMS, while others prefer less forested areas. Scientists studying malaria in the Amazon in South America suspect that malaria transmission increases shortly after deforestation but decreases six to eight years later. Some studies have tested this 'frontier malaria' theory but the results have been conflicting. Fewer studies have tested this theory in Southeast Asia. But deforestation has been blamed for recent malaria outbreaks in the GMS. Using data on malaria testing and forest cover in the GMS, Rerolle et al. show that deforestation around villages increases malaria transmission in the first two years and decreases malaria rates later. This trend was driven mostly by a type of malaria called Plasmodium falciparum and was less strong for Plasmodium vivax. The location of deforested areas also mattered. Deforestation within one to 10 kilometer of villages did not affect malaria rates. Deforestation further away in about a 30 kilometer radius did affect malaria transmission. Rerolle et al. suggest this may be because villagers have to spend longer times trekking through forests to hunt or harvest wood when the wider area is deforested. Currently, National Malaria Control Programs in the GMS focus their efforts on reducing forest-related transmission. This study strengthens the evidence supporting this approach. The results also suggest that different malaria elimination strategies may be necessary for different types of malaria parasite. Using this new information could help malaria control programs better target resources or educate villagers on how to protect themselves. The innovative methods used by Rerolle et al. reveal a more complex role of deforestation in malaria transmission and may inspire other scientists to think more carefully about environmental drivers of malaria.

Serological surveys to estimate cumulative incidence of SARS-CoV-2 infection in adults (Sero-MAss study), Massachusetts, July-August 2020: a mail-based cross-sectional study.

BACKGROUND: The SARS-CoV-2 pandemic is an unprecedented global health crisis. The state of Massachusetts was especially impacted during the initial stages; however, the extent of asymptomatic transmission remains poorly understood due to limited asymptomatic testing in the "first wave." To address this gap, a geographically representative and contact-free seroprevalence survey was conducted in July-August 2020, to estimate prior undetected SARS-CoV-2 infections. METHODS: Students, faculty, librarians and staff members at the University of Massachusetts, Amherst without a previous COVID-19 diagnosis were invited to participate in this study along with one member of their household in June 2020. Two separate sampling frames were generated from administrative lists: all undergraduates and their household members (primary sampling group) were randomly selected with probability proportional to population size. All staff, faculty, graduate students and librarians (secondary sampling group) were selected as a simple random sample. After informed consent and a socio-behavioral survey, participants were mailed test kits and asked to return self-collected dried blood spot (DBS) samples. Samples were analyzed via ELISA for anti-SARS-CoV-2 IgG antibodies, and then IgM antibodies if IgG-positive. Seroprevalence estimates were adjusted for survey non-response. Binomial models were used to assess factors associated with seropositivity in both sample groups separately. RESULTS: Approximately 27,000 persons were invited via email to assess eligibility. Of the 1,001 individuals invited to participate in the study, 762 (76%) returned blood samples for analysis. In the primary sampling group 548 returned samples, of which 230 enrolled a household member. Within the secondary sampling group of 214 individuals, 79 enrolled a household member. In the primary sample group, 36 (4.6%) had IgG antibodies detected for an estimated weighed prevalence for this population of 5.3% (95% CI: 3.5 to 8.0). In the secondary sampling group, 10 (3.4%) of 292 individuals had IgG antibodies detected for an estimated adjusted prevalence of 4.0% (95% CI: 2.2 to 7.4). No samples were IgM positive. No association was found in either sample group between seropositivity and self-reported work duties or customer-facing hours. In the primary sampling group, self-reported febrile illness since Feb 2020, male sex, and minority race (Black or American Indian/Alaskan Native) were associated with seropositivity. No factors except geographic regions within the state were associated with evidence of prior SARS-CoV-2 infection in the secondary sampling group. INTERPRETATION: This study provides insight into the seroprevalence of university-related populations and their household members across the state of Massachusetts during the summer of 2020 of the pandemic and helps to fill a critical gap in estimating the levels of sub-clinical and asymptomatic infection. Estimates like these can be used to calibrate models that estimate levels of population immunity over time to inform public health interventions and policy.

The impact of transfluthrin on the spatial repellency of the primary malaria mosquito vectors in Vietnam: Anopheles dirus and Anopheles minimus.

BACKGROUND: The complexity of mosquito-borne diseases poses a major challenge to global health efforts to mitigate their impact on people residing in sub-tropical and tropical regions, to travellers and deployed military personnel. To supplement drug- and vaccine-based disease control programmes, other strategies are urgently needed, including the direct control of disease vectors. Modern vector control research generally focuses on identifying novel active ingredients and/or innovative methods to reduce human-mosquito interactions. These efforts include the evaluation of spatial repellents, which are compounds capable of altering mosquito feeding behaviour without direct contact with the chemical source. METHODS: This project examined the impact of airborne transfluthrin from impregnated textile materials on two important malaria vectors, Anopheles dirus and Anopheles minimus. Repellency was measured by movement within taxis cages within a semi-field environment at the National Institute of Hygiene and Epidemiology in Hanoi, Vietnam. Knockdown and mortality were measured in adult mosquito bioassay cages. Metered-volume air samples were collected at a sub-set of points in the mosquito exposure trial. RESULTS: Significant differences in knockdown/mortality were observed along a gradient from the exposure source with higher rates of knockdown/mortality at 2 m and 4 m when compared with the furthest distance (16 m). Knockdown/mortality was also greater at floor level and 1.5 m when compared to 3 m above the floor. Repellency was not significantly different except when comparing 2 m and 16 m taxis cages. Importantly, the two species reacted differently to transfluthrin, with An. minimus being more susceptible to knockdown and mortality. The measured concentrations of airborne transfluthrin ranged from below the limit of detection to 1.32 ng/L, however there were a limited number of evaluable samples complicating interpretation of these results. CONCLUSIONS: This study, measuring repellency, knockdown and mortality in two malaria vectors in Vietnam demonstrates that both species are sensitive to airborne transfluthrin. The differences in magnitude of response between the two species requires further study before use in large-scale vector control programmes to delineate how spatial repellency would impact the development of insecticide resistance and the disruption of biting behaviour.

FluSense: A Contactless Syndromic Surveillance Platform for Influenza-Like Illness in Hospital Waiting Areas.

We developed a contactless syndromic surveillance platform FluSense that aims to expand the current paradigm of influenza-like illness (ILI) surveillance by capturing crowd-level bio-clinical signals directly related to physical symptoms of ILI from hospital waiting areas in an unobtrusive and privacy-sensitive manner. FluSense consists of a novel edge-computing sensor system, models and data processing pipelines to track crowd behaviors and influenza-related indicators, such as coughs, and to predict daily ILI and laboratory-confirmed influenza caseloads. FluSense uses a microphone array and a thermal camera along with a neural computing engine to passively and continuously characterize speech and cough sounds along with changes in crowd density on the edge in a real-time manner. We conducted an IRB-approved 7 month-long study from December 10, 2018 to July 12, 2019 where we deployed FluSense in four public waiting areas within the hospital of a large university. During this period, the FluSense platform collected and analyzed more than 350,000 waiting room thermal images and 21 million non-speech audio samples from the hospital waiting areas. FluSense can accurately predict daily patient counts with a Pearson correlation coefficient of 0.95. We also compared signals from FluSense with the gold standard laboratory-confirmed influenza case data obtained in the same facility and found that our sensor-based features are strongly correlated with laboratory-confirmed influenza trends.

Study protocol for a cluster-randomized split-plot design trial to assess the effectiveness of targeted active malaria case detection among high-risk populations in Southern Lao PDR (the AcME-Lao study).

Introduction: Novel interventions are needed to accelerate malaria elimination, especially in areas where asymptomatic parasitemia is common, and where transmission generally occurs outside of village-based settings. Testing of community members linked to a person with clinical illness (reactive case detection, RACD) has not shown effectiveness in prior studies due to the limited sensitivity of current point-of-care tests. This study aims to assess the effectiveness of active case finding in village-based and forested-based settings using novel high-sensitivity rapid diagnostic tests in Lao People's Democratic Republic (Lao PDR). Methods and analysis: This study is a cluster-randomized split-plot design trial. The interventions include village-based mass test and treat (MTAT), focal test and treat in high-risk populations (FTAT), and the combination of these approaches, using high-sensitivity rapid diagnostic tests (HS-RDTs) to asses P. falciparum infection status. Within four districts in Champasak province, Lao PDR fourteen health center-catchment areas will be randomized to either FTAT or control; and within these HCCAs, 56 villages will be randomized to either MTAT or control. In intervention areas, FTAT will be conducted by community-based peer navigators on a routine basis, and three separate rounds of MTAT are planned. The primary study outcome will be PCR-based Plasmodium falciparum prevalence after one year of implementation. Secondary outcomes include malaria incidence; interventional coverage; operational feasibility and acceptability; and cost and cost- effectiveness. Ethics and dissemination: Findings will be reported on clinicaltrials.gov, in peer-reviewed publications and through stakeholder meetings with Ministry of Health and community leaders in Lao PDR and throughout the Greater Mekong Subregion. Trial registration: clinicaltrials.gov NCT03783299 (21/12/2018).

Prevalence and risk factors for asymptomatic malaria and genotyping of glucose 6-phosphate (G6PD) deficiencies in a vivax-predominant setting, Lao PDR: implications for sub-national elimination goals.

BACKGROUND: Lao People Democratic Republic (PDR; Laos), a landlocked country in Southeast Asia, has made important progress in reducing malaria morbidity and mortality in the past 5-6 years, and the northern provinces have very low reported incidence. To support national progress towards elimination, it is critical to verify and understand these changes in disease burden. METHODS: A two-stage cluster cross-sectional survey was conducted in four districts within four northern provinces (Khua, Phongsaly Province; Paktha, Bokeo Province; Nambak, Luang Prabang, and Muang Et, Huaphanh Province). During September and October 2016, demographics and malaria risk factors were collected from a total of 1492 households. A total of 5085 persons consented to collection of blood samples for testing, by rapid diagnostic test (RDT) and polymerase chain reaction (PCR)-based testing. Risk factors for infection were examined using logistic regression; and a randomized subset of males was tested for glucose-6-phosphate dehydrogenase (G6PD) deficiencies using a combined PCR and sequencing approach. RESULTS: There were zero positives by RDT, and PCR detected Plasmodium infections in 39 (0.77%; 95% CI 0.40-1.47%) of 5082 analysable samples. The species distribution was Plasmodium vivax (28 total); Plasmodium falciparum/P. vivax (5); P. falciparum (3), Plasmodium malariae (2), and P. vivax/P. malariae (1). In multivariable analysis, the main risk factors included having any other cases within the household [aOR 12.83 (95% CI 4.40 to 37.38), p < 0.001]; and lack of bed net ownership within the household [aOR 10.91 (95% 5.42-21.94), p < 0.001]; age, sex and forest-travel were not associated with parasitaemia. A total of 910 males were tested for the six most common G6PDd in SE Asia; and 30 (3.3%; 95% CI 2.1-5.1%) had a G6PD variant allele associated with G6PD deficiency, with the majority being the Union (14) and Viangchan (11) polymorphisms, with smaller numbers of Canton and Mahidol. CONCLUSION: This is the first rigorous PCR-based population survey for malaria infection in Northern Lao PDR, and found a very low prevalence of asymptomatic Plasmodium infections by standard PCR methods, with P. vivax predominating in the surveyed districts. Clustering of cases within households, and lack of a bed nets suggest reactive case detection, and scale-up of coverage should be prioritized. The predominance of infections with P. vivax, combined with moderate levels of serious G6PD deficiencies highlight the need for careful rollout of primaquine towards elimination goals.