Natalie M. Bowman

Background: Particulate air pollution (specifically <2·5µm diameter [PM2·5]), temperature, and Trypanosoma cruzi (Tc) each are deleterious to pregnancy. PM2·5 crosses the placenta, weakening the trophoblastic layer through inflammation. Sustained exposure to high heat causes chronic intrauterine inflammation, affecting placental formation. Tc parasitemia increases during pregnancy, causing placental degradation through inflammation and resulting in congenital Chagas disease (cCD) in approximately one-in-twenty Tc(+) pregnancies. The interaction of PM2·5 and temperature during pregnancy with cCD is unstudied.Methods: We analyzed a Bolivian pregnancy cohort (2006-2014) including 581 Tc(+) pregnancies with 46 congenitally infected infants. European Space Agency-Copernicus estimates of monthly mean wet-bulb temperature and PM2·5 were used to create individual monthly pregnancy exposures for 12-months prior-to-birth. Lagged-Weighted Quantile Sum regression analysis was conducted to determine the time-varying association of these exposures with cCD.Findings: cCD was significantly associated with exposure to higher temperatures and PM2·5 pre-conception and high PM2·5 in the last three months of pregnancy.Interpretation: Systemic inflammation from PM2·5 and high temperatures likely depress the already modulated maternal immune system allowing higher parasitemia during pregnancy. Inflammatory responses to PM2·5, temperature, and Tc may weaken the placental barrier, allowing the parasite to more easily cross the marginal sinus and the trophoblastic layer of the intervillous space and infect the fetus. In urban areas, vector-bone Tc transmission is now uncommon; however, there is still a significant incidence of cCD. Mitigating the effects exposure to high PM2·5 and temperatures during pregnancy is an important component to preventing cCD.

Chagas disease is a major protozoan infection in the Americas, causing approximately 12,000 deaths each year. It is caused by Trypanosoma cruzi , and can be transmitted transplacentally, leading to congenital Chagas disease, a silent route that carries substantial risk for newborns. However, the mechanisms underlying congenital Chagas transmission are poorly understood. Here, we evaluated whether T. cruzi infection alters the placental microenvironment and systemic physiology, and whether such alterations are associated with congenital transmission. Integrating bulk RNA sequencing, proteomics, and spatial transcriptomics, we show that T. cruzi infection elicits profound molecular remodeling in both placenta and peripheral blood, regardless of transmission status. Transmitting mothers exhibit a distinct transcriptional signature enriched for inflammatory and tissue-remodeling pathways. Notably, peripheral blood profiles mirrored some placental alterations. A panel of inflammatory serum proteins showed promising predictive potential for transmission risk, with implications for prenatal monitoring. Together, these findings support a fundamental shift in the conceptual framework of congenital Chagas disease, from a transmission-centered model to one that recognizes infection-driven placental damage as a pathological spectrum and identifies peripheral blood as a promising, non-invasive source of predictive biomarkers for adverse pregnancy outcomes. This framework motivates the further application of single-cell-resolution approaches to refine models of congenital Chagas pathogenesis and the systematic analysis of maternal peripheral blood during pregnancy to enable early risk stratification and the development of predictive tools for adverse outcomes.

Workers in food processing industries are subject to many occupational health risks and disparities, but little is known about their risk of tickborne diseases. We examined a cohort of Latino individuals working in the meat packing, produce processing, and farming industries and their family members in central North Carolina, where incidence of tickborne infections is high. Blood samples were tested for IgG antibodies against Spotted Fever Group Rickettsiosis (SFGR) and Ehrlichia chaffeensis. Covariates of interest included age, sex, primary language, work industry, indoor vs. outdoor work, home characteristics, medical comorbidities, and travel history. Among 201 Latino food processing workers and their family members, the seroprevalence of SFGR and Ehrlichia was 14.9% and 19.9%, respectively. Almost a third of participants were seropositive for at least one infection. SFGR seropositive individuals were significantly older than seronegative individuals (median 45 [interquartile range 35–55] vs. 33 [14–45] years, p < 0.001), while Ehrlichia seropositivity appeared to have a bimodal distribution by age, with peaks in children under age 10 and adults in their forties and fifties. Farm workers had higher seroprevalence of SFGR (25.0%) than other workers (13.5%), although this did not reach statistical significance (p = 0.13). Having a seropositive household member for either infection was a risk factor for seropositivity for the same infection, adjusted for age and household clustering (adjusted OR [aOR] 8.26, 95% CI [confidence interval] 3.27-20.90 for SFGR; aOR 11.24, 95% CI 4.24-29.80 for Ehrlichia). Seroprevalence for SFGR and Ehrlichia was similar between index workers and household members when adjusted for age. Our findings indicate that Latino food processing communities in North Carolina have high exposure to tickborne disease, and older age and having seropositive household members are key risk factors.

Diagnostic delays prevent most Chagas disease patients from receiving timely therapy during the acute phase when treatment is effective. qPCR-based diagnostic methods provide high sensitivity during this phase but require specialized equipment and complex protocols. More simple and cost-effective tools are urgently needed to optimize early Chagas disease diagnosis in low-income endemic regions. Here, we present a loop-mediated isothermal amplification (LAMP) that targets a highly conserved region in the HSP70 gene of Trypanosoma cruzi, the causative agent of Chagas disease. This assay demonstrates species-specific amplification across multiple parasite genetic lineages while maintaining stability after 2 hours of incubation and at least 8 months of storage at −20°C. Moreover, the assay is at least 12 times less expensive than the TaqMan qPCR that is currently routinely used for acute Chagas diagnostics. Population-based validation in 100 infants born to Chagas-positive mothers in Santa Cruz, Bolivia, yielded a specificity of 100% and sensitivity exceeding 77% when compared to a TaqMan qPCR that targets satellite DNA. This cost-effective assay holds promise for large-scale diagnosis of Chagas disease in endemic regions with limited resources.

Background: Generation time, representing the interval between infection events in primary and secondary cases, is important for understanding disease transmission dynamics including predicting the effective reproduction number (Rt), which informs public health decisions. While previous estimates of SARS-CoV-2 generation times have been reported for early Omicron variants, there is a lack of data for subsequent sub-variants, such as XBB. Methods: We estimated SARS-CoV-2 generation times using data from the Respiratory Virus Transmission Network – Sentinel (RVTN-S) household transmission study conducted across seven U.S. sites from December 2021 to May 2023. The study spanned three Omicron sub-periods dominated by the sub-variants BA.1/2, BA.4/5, and XBB. We employed a Susceptible-Exposed-Infectious-Recovered (SEIR) model with a Bayesian data augmentation method that imputes unobserved infection times of cases to estimate the generation time. Findings: The estimated mean generation time for the overall Omicron period was 3.5 days (95% credible interval, CrI: 3.3-3.7). During the sub-periods, the estimated mean generation times were 3.8 days (95% CrI: 3.4-4.2) for BA.1/2, 3.5 days (95% CrI: 3.3-3.8) for BA.4/5, and 3.5 days (95% CrI: 3.1-3.9) for XBB. Interpretation: Our study provides estimates of generation times for the Omicron variant, including the sub-variants BA.1/2, BA.4/5, and XBB. These up-to-date estimates specifically address the gap in knowledge regarding these sub-variants and are consistent with earlier studies. They enhance our understanding of SARS-CoV-2 transmission dynamics by aiding in the prediction of Rt, offering insights for improving COVID-19 modeling and public health strategies. Funding: Centers for Disease Control and Prevention, and National Center for Advancing Translational Sciences.

The generation time, representing the interval between infections in primary and secondary cases, is essential for understanding and predicting the transmission dynamics of seasonal influenza, including the real-time effective reproduction number (Rt). However, comprehensive generation time estimates for seasonal influenza, especially post the 2009 influenza pandemic, are lacking. We estimated the generation time utilizing data from a 7-site case-ascertained household study in the United States over two influenza seasons, 2021/2022 and 2022/2023. More than 200 individuals who tested positive for influenza and their household contacts were enrolled within 7 days of the first illness in the household. All participants were prospectively followed for 10 days completing daily symptom diaries and collecting nasal swabs, which were tested for influenza via RT-PCR. We analyzed these data by modifying a previously published Bayesian data augmentation approach that imputes infection times of cases to obtain both intrinsic (assuming no susceptible depletion) and realized (observed within household) generation times. We assessed the robustness of the generation time estimate by varying the incubation period, and generated estimates of the proportion of transmission before symptomatic onset, infectious period, and latent period. We estimated a mean intrinsic generation time of 3.2 (95% credible interval, CrI: 2.9-3.6) days, with a realized household generation time of 2.8 (95% CrI: 2.7-3.0) days. The generation time exhibited limited sensitivity to incubation period variation. Estimates of the proportion of transmission that occurred before symptom onset, the infectious period, and the latent period were sensitive to variation in incubation periods. Our study contributes to the ongoing efforts to refine estimates of the generation time for influenza. Our estimates, derived from recent data following the COVID-19 pandemic, are consistent with previous pre-pandemic estimates, and will be incorporated into real-time Rt estimation efforts.

Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi , affects an estimated 10.5 million people worldwide and remains a leading cause of infectious cardiomyopathy in Latin America. Although infection is lifelong without treatment, only 20–30% of chronically infected individuals progress from an asymptomatic stage to clinically significant cardiac disease, and current antiparasitic therapies are limited by toxicity and variable efficacy. Reliable biomarkers capable of predicting disease progression would improve clinical risk stratification and support therapeutic development. Here, we performed a metabolomics study to identify serum biomarkers predictive of progression from asymptomatic infection to cardiac CD. Untargeted liquid chromatography–mass spectrometry profiling using complementary chromatographic platforms and univariate statistics, machine learning feature selection, and receiver operating characteristic (ROC) analysis were performed to identify candidate biomarkers. These biomarkers were validated by targeted analysis. We identified eight individual metabolite biomarkers and 45 combinatorial panels predictive of progression status, including 10 panels that met sensitivity and specificity criteria defined in the target product profile for CD treatment-response biomarkers. These findings demonstrate that circulating metabolites measured at baseline can predict future cardiac disease progression and provide a foundation for clinically deployable prognostic tools in chronic Chagas disease.

Tuberculosis remains one of the leading causes of death worldwide, especially in low- and middle-income countries. Tuberculosis treatment and control efforts are hindered by the difficulty in making the diagnosis, as currently available diagnostic tests are too slow, too expensive, or not sufficiently sensitive. Recombinase polymerase amplification (RPA) is a novel technique that allows for the amplification of DNA rapidly, at constant temperature, and with minimal expense. We calculated and compared the limit of detection, sensitivity, and specificity of two RPA-based assays for the diagnosis of pulmonary tuberculosis, using two sets of published primers. We also calculated and compared the assays’ limits of detection and compared their performance using two different DNA extraction methods prior to amplification (a commercially available DNA extraction kit vs. the chelex method). The RPA-lateral flow assay had a limit of detection of 5 fg/μL of DNA, a sensitivity of 53.2%, and a specificity of 93.3%, while the real time-RPA assay had a limit of detection of 25 fg/μL of DNA, a sensitivity of 85.1%, and a specificity of 93.3%. There was no difference in assay performance when DNA extraction was carried out using the commercial kit vs. the chelex method. The real-time RPA assay has adequate sensitivity and specificity for the diagnosis of pulmonary tuberculosis and could be a viable diagnostic tool in resource-limited settings, but the lateral flow assay did not perform as well, perhaps due to the fact we used stored sputum specimens from a biorepository. More work is needed to optimize the RPA-lateral flow assay, to get a more accurate estimate of its specificity and sensitivity using prospectively collected specimens, and to develop both assays into point-of-care tests that can be easily deployed in the field.