Temperature is a key factor influencing microbial growth rates and yields. In literature, the influence of temperature on growth is studied either on yields or rates but not both at the same time. Moreover, studies often report the influence of a specific set of temperatures using rich culture media containing complex ingredients (such as yeast extract) which chemical composition cannot be precisely specified. Here, we present a complete dataset for the growth of Escherichia coli K12 NCM3722 strain in a minimal medium containing glucose as the sole energy and carbon source for the computation of growth yields and rates at each temperature from 27 to 45°C. For this purpose, we monitored the growth of E. coli by automated optical density (OD) measurements in a thermostated microplate reader. At each temperature full OD curves were reported for 28 to 40 microbial cultures growing in parallel wells. Additionally, a correlation was established between OD values and the dry mass of E. coli cultures. For that, 21 dilutions were prepared from triplicate cultures and optical density was measured in parallel with the microplate reader (ODmicroplate) and a UV-Vis spectrophotometer (ODUV-vis) and correlated to duplicate dry biomass measurements. The correlation was used to compute growth yields in terms of dry biomass.
Nontuberculous mycobacteria (NTM) are ubiquitous microorganisms naturally resistant to antibiotics and disinfectants that can colonize drinking water supply systems. Information regarding the spread of NTM in specifically South America and Colombia is limited. We aimed to identify and characterize NTM present in tap water samples from Cali, Colombia. Drinking water samples and faucet biofilm swabs were collected in 18 places, including the city’s three main water treatment plants (WTPs). Filter-trapped material and eluates (0.45 μm) from swab washes were plated in 7H11 agar plates. Suspected colonies were evaluated microscopically, and NTM species were identified based on the rpoB gene. Antibiotic susceptibility testing was also performed. Fifty percent (9/18) of sampling points were positive for NTM (including two WTPs), from which 16 different isolates were identified: Mycobacterium mucogenicum (8/16), M. phocaicum (3/16), M. chelonae (2/16), M. mageritense (2/16), and M. fortuitum (1/16), all rapidly growing mycobacteria. A susceptibility profile was obtained from 68.75% (11/16) of the isolates. M. chelonae was the most resistant species. All NTM isolated are potentially responsible for human diseases; our findings might provide a baseline for exploring NTM transmission dynamics and clinical characterization, as well as potential associations between NTM species found in drinking water and isolates from patients.
Wastewater based epidemiology (WBE) is increasingly used to provide decision makers with actionable data about community health. WBE efforts to date have primarily focused on sewer-transported wastewater in high-income countries, but at least 1.8 billion people in low-and middle-income countries (LMIC) use onsite sanitation systems such as pit latrines and septic tanks. Like wastewater, fecal sludges from such systems offer similar advantages in community pathogen monitoring and other epidemiological applications. To evaluate the distribution of enteric pathogens inside pit latrines–which could inform sampling methods for WBE in LMIC settings unserved by sewers–we collected fecal sludges from the surface, mid-point, and maximum-depth of 33 pit latrines in urban and peri-urban Malawi and analyzed the 99 samples for 20 common enteric pathogens via multiplex quantitative reverse transcription PCR. Using logistic regression adjusted for household population, latrine sharing, the presence of a concrete floor or slab, water source, and anal cleansing materials, we found no significant difference in the odds of detecting the 20 pathogens from the mid-point (adjusted odds ratio, aOR = 1.1; 95% confidence interval = 0.73, 1.6) and surface samples (aOR = 0.80, 95% CI = 0.54, 1.2) compared with those samples taken from the maximum depth. Our results suggest that, for the purposes of routine pathogen monitor-ing, pit latrine sampling depth does not strongly influence the odds of detecting enteric pathogens by molecular methods. A single sample from the pit latrines’ surface, or a composite of surface samples, may be preferred as the most recent material contributed to the pit and may be easiest to collect.
A series of one-dimensional column experiments was conducted to examine the effects of tube length on the transport and deposition of 4-ethoxybenzoic acid functionalized multi-wall carbon nanotubes (MWCNTs) in water-saturated porous media. Aqueous MWCNTs suspensions were prepared to yield three distributions of tube lengths; 0.02-1.3 μm (short), 0.2-7.5 μm (medium), and 0.2-21.4 μm (long). Results of the column studies showed that MWCNT retention increased with increasing tube length. Nevertheless, more than 76% of the MWCNT mass delivered to the columns was detected in effluent samples under all experimental conditions, indicating that the functionalized MWCNTs were readily transported through 40-50 mesh Ottawa sand. Examination of MWCNT length distributions in the effluent samples revealed that nanotubes with lengths greater than 8 μm were preferentially deposited. In addition, measured retention profiles exhibited the greatest MWCNT deposition near the column inlet, which was most pronounced for the long MWCNTs, and decreased sharply with travel distance. Scanning electron microscope (SEM) images showed that MWCNTs were deposited on sand surfaces over the entire column length, while larger MWCNT bundles were retained at grain intersections and near the column inlet. A mathematical model based on clean bed filtration theory (CBFT) was unable to accurately simulate the measured retention profile data, even after varying the weighting function and incorporating a nonuniform attachment rate coefficient expression. Modification of the mathematical model to account for physical straining greatly improved predictions of MWCNT retention, yielding straining rate coefficients that were four orders-of-magnitude greater than corresponding attachment rate coefficients. Taken in concert, these experimental and modeling results demonstrate the potential importance of, and need to consider, particle straining and tube length distribution when describing MWCNT transport in water-saturated porous media.
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Kevin J Zhu;
Brittany Suttner;
Jackie Knee;
Drew Capone;
Christine Moe;
Christine E Stauber;
Kostas T Konstantinidis;
Thomas E Wallach;
Amy J Pickering;
Joe Brown
An end goal of fecal source tracking (FST) is to provide information on risk of transmission of waterborne illnesses associated with fecal contamination. Ideally, concentrations of FST markers in ambient waters would reflect exposure risk. Human mtDNA is an FST marker that is exclusively human in origin and may be elevated in feces of individuals experiencing gastrointestinal inflammation. In this study, we examined whether human mtDNA is elevated in fecal samples from individuals with symptomatic norovirus infections using samples from the United States (US), Mozambique, and Bangladesh. We quantified hCYTB484 (human mtDNA) and HF183/BacR287 (human-associated Bacteroides) FST markers using droplet digital polymerase chain reaction. We observed the greatest difference in concentrations of hCYTB484 when comparing samples from individuals with symptomatic norovirus infections versus individuals without norovirus infections or diarrhea symptoms: log10 increase of 1.42 in US samples (3,820% increase, p-value = 0.062), 0.49 in Mozambique (308% increase, p-value = 0.061), and 0.86 in Bangladesh (648% increase, p-value = 0.035). We did not observe any trends in concentrations of HF183/BacR287 in the same samples. These results suggest concentrations of fecal mtDNA may increase during symptomatic norovirus infection and that mtDNA in environmental samples may represent an unambiguously human source-tracking marker that correlates with enteric pathogen exposure risk.
Introduction: Despite recommendations for COVID-19 primary series completion and booster doses for children and adolescents, coverage has been less than optimal, particularly in some subpopulations. This study explored disparities in childhood/adolescent COVID-19 vaccination, parental intent to vaccinate their children and adolescents, and reasons for non-vaccination in the US. Methods: Using the U.S. Census Bureau’s Household Pulse Survey (HPS), we analyzed households with children aged <18 years using data collected from September 14 to November 14, 2022 (n = 44,929). Child and adolescent COVID-19 vaccination coverage (≥1 dose, completed primary series, and booster vaccination) and parental intentions toward vaccination were assessed by sociodemographic characteristics. Factors associated with child and adolescent vaccination coverage were examined using multivariable regression models. Reasons for non-vaccination were assessed overall, by the child’s age group and respondent’s age group. Results: Overall, approximately half (50.1%) of children aged < 18 years were vaccinated against COVID-19 (≥1 dose). Completed primary series vaccination was 44.2% among all children aged <18 years. By age group, completed primary series was 13.2% among children <5 years, 43.9% among children 5–11 years, and 63.3% among adolescents 12–17 years. Booster vaccination among those who completed the primary series was 39.1% among children 5–11 years and 55.3% among adolescents 12–17 years. Vaccination coverage differed by race/ethnicity, educational attainment, household income, region, parental COVID-19 vaccination status, prior COVID-19 diagnosis, child’s age group, and parental age group. Parental reluctance was highest for children aged <5 years (46.8%). Main reasons for non-vaccination among reluctant parents were concerns about side effects (53.3%), lack of trust in COVID-19 vaccines (48.7%), and the belief that children do not need a COVID-19 vaccine (38.8%). Conclusion: Disparities in COVID-19 vaccination coverage among children and adolescents continue to exist. Further efforts are needed to increase COVID-19 primary series and booster vaccination and parental confidence in vaccines.
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Zhihong Qian;
Dylan H Morris;
Annika Avery;
Karen A Kormuth;
Valerie Le Sage;
Michael M Myerburg;
James O Lloyd-Smith;
Linsey C Marr;
Seema S Lakdawala
Respiratory viruses can be transmitted by multiple modes, including contaminated surfaces, commonly referred to as fomites. Efficient fomite transmission requires that a virus remain infectious on a given surface material over a wide range of environmental conditions, including different relative humidities. Prior work examining the stability of influenza viruses on surfaces has relied upon virus grown in media or eggs, which does not mimic the composition of virus-containing droplets expelled from the human respiratory tract. In this study, we examined the stability of the 2009 pandemic H1N1 (H1N1pdm09) virus on a variety of nonporous surface materials at four different humidities. Importantly, we used virus grown in primary human bronchial epithelial cell (HBE) cultures from different donors to recapitulate the physiological microenvironment of expelled viruses. We observed rapid inactivation of H1N1pdm09 on copper under all experimental conditions. In contrast to copper, viruses were stable on polystyrene plastic, stainless steel, aluminum, and glass, at multiple relative humidities, but greater decay on acrylonitrile butadiene styrene (ABS) plastic was observed at short time points. However, the half-lives of viruses at 23% relative humidity were similar among noncopper surfaces and ranged from 4.5 to 5.9 h. Assessment of H1N1pdm09 longevity on nonporous surfaces revealed that virus persistence was governed more by differences among HBE culture donors than by surface material. Our findings highlight the potential role of an individual's respiratory fluid on viral persistence and could help explain heterogeneity in transmission dynamics. IMPORTANCE Seasonal epidemics and sporadic pandemics of influenza cause a large public health burden. Although influenza viruses disseminate through the environment in respiratory secretions expelled from infected individuals, they can also be transmitted by contaminated surfaces where virus-laden expulsions can be deposited. Understanding virus stability on surfaces within the indoor environment is critical to assessing influenza transmission risk. We found that influenza virus stability is affected by the host respiratory secretion in which the virus is expelled, the surface material on which the droplet lands, and the ambient relative humidity of the environment. Influenza viruses can remain infectious on many common surfaces for prolonged periods, with half-lives of 4.5 to 5.9 h. These data imply that influenza viruses are persistent in indoor environments in biologically relevant matrices. Decontamination and engineering controls should be used to mitigate influenza virus transmission.
BACKGROUND: Safe water, sanitation, and hygiene (WaSH) is important for health, livelihoods, and economic development, but WaSH programs have often underdelivered on expected health benefits. Underperformance has been attributed partly to poor ability to retain effectiveness following adaptation to facilitate WaSH programs' implementation in diverse contexts. Adaptation of WaSH interventions is common but often not done systematically, leading to poor outcomes. Models and frameworks from the adaptation literature have potential to improve WaSH adaptation to facilitate implementation and retain effectiveness. However, these models and frameworks were designed in a healthcare context, and WaSH interventions are typically implemented outside traditional health system channels. The purpose of our work was to develop an adaptation model tailored specifically to the context of WaSH interventions. METHODS: We conducted a scoping review to identify key adaptation steps and identify tools to support systematic adaptation. To identify relevant literature, we conducted a citation search based on three recently published reviews on adaptation. We also conducted a systematic database search for examples of WaSH adaptation. We developed a preliminary model based on steps commonly identified across models in adaptation literature, and then tailored the model to the WaSH context using studies yielded by our systematic search. We compiled a list of tools to support systematic data collection and decision-making throughout adaptation from all included studies. RESULTS AND CONCLUSIONS: Our model presents adaptation steps in five phases: intervention selection, assessment, preparation, implementation, and sustainment. Phases for assessment through sustainment are depicted as iterative, reflecting that once an intervention is selected, adaptation is a continual process. Our model reflects the specific context of WaSH by including steps to engage non-health and lay implementers and to build consensus among diverse stakeholders with potentially competing priorities. We build on prior adaptation literature by compiling tools to support systematic data collection and decision-making, and we describe how they can be used throughout adaptation steps. Our model is intended to improve program outcomes by systematizing adaptation processes and provides an example of how systematic adaptation can occur for interventions with health goals but that are implemented outside conventional health system channels.
Exposure to vehicular emissions has been linked to numerous adverse health effects. In response to the arising concerns, near-road monitoring is conducted to better characterize the impact of mobile source emissions on air quality and exposure in the near-road environment. An intensive measurement campaign measured traffic-related air pollutants (TRAPs) and related data (e.g., meteorology, traffic, regional air pollutant levels) in Atlanta, along one of the busiest highway corridors in the US. Given the complexity of the near-road environment, the study aimed to compare two near-road monitors, located in close proximity to each other, to assess how observed similarities and differences between measurements at these two sites inform the siting of other near-road monitoring stations. TRAP measurements, including carbon monoxide (CO) and nitrogen dioxide (NO2), are analyzed at two roadside monitors in Atlanta, GA located within 325 m of each other. Both meteorological and traffic conditions were monitored to assess the temporal impact of these factors on traffic-related pollutant concentrations. The meteorological factors drove the diurnal variability of primary pollutant concentration more than traffic count. In spite of their proximity, while the CO and NO2 concentrations were correlated with similar diurnal variations, pollutant concentrations at the two closely sited monitors differed, likely due to the differences in the siting characteristics reducing the dispersion of the primary emissions out of the near-road environment. Overall, the near-road TRAP concentrations at all sites were not as elevated as seen in prior studies, supporting that decreased vehicle emissions have led to significant reductions in TRAP levels, even along major interstates. Further, the differences in the observed levels show that use of single near-road observations will not capture pollutant levels representative of the local near-road environment and that additional approaches (e.g., air quality models) are needed to characterize exposures.
The western United States has experienced increasing wildfire activities, which have negative effects on human health. Epidemiological studies on fine particulate matter (PM2.5) from wildfires are limited by the lack of accurate high-resolution PM2.5 exposure data over fire days. Satellite-based aerosol optical depth (AOD) data can provide additional information in ground PM2.5 concentrations and has been widely used in previous studies. However, the low background concentration, complex terrain, and large wildfire sources add to the challenge of estimating PM2.5 concentrations in the western United States. In this study, we applied a Bayesian ensemble model that combined information from the 1 km resolution AOD products derived from the Multi-angle Implementation of Atmospheric Correction (MAIAC) algorithm, Community Multiscale Air Quality (CMAQ) model simulations, and ground measurements to predict daily PM2.5 concentrations over fire seasons (April to September) in Colorado for 2011–2014. Our model had a 10-fold cross-validated R2 of 0.66 and root-mean-squared error of 2.00 μg/m3, outperformed the multistage model, especially on the fire days. Elevated PM2.5 concentrations over large fire events were successfully captured. The modeling technique demonstrated in this study could support future short-term and long-term epidemiological studies of wildfire PM2.5.