Search

BackgroundThe COVID-19 pandemic has generated a demand for timely data, resulting in a surge of mobile phone surveys for tracking the impacts of and responses to the pandemic. Mobile phone surveys have become a preferred mode of data collection across low- and middle-income countries. ObjectiveThis study piloted 2 population-based, cross-sectional mobile phone surveys among Sri Lankan residents in 2020 and 2021 during the COVID-19 pandemic. The surveys aimed to gather data on knowledge, attitudes, and practices, vaccine acceptability, availability, and barriers to COVID-19 testing, and use of a medicine distribution service. MethodsThe study used Surveda, an open-source survey tool developed by the NCD (noncommunicable disease) Mobile Phone Survey Data 4 Health Initiative, for data collection and management. The surveys were conducted through interactive voice response using automated, prerecorded messages in Sinhala, Tamil, and English. The sample design involved random sampling of mobile phone numbers, stratified by sex, proportional to the general population. Eligibility criteria varied between surveys, targeting adults aged 35 years and older with any noncommunicable disease for the first survey and all adults for the second survey. The data were adjusted to population estimates, and statistical analysis was conducted using SAS (SAS Institute) and R software (R Core Team). Descriptive statistics, Rao-Scott chi-square tests, and z tests were used to analyze the data. Response rates, cooperation rates, and productivity of the sampling approach were calculated. ResultsIn the first survey, n=5001, the overall response rate was 7.5%, with a completion rate of 85.6%. In the second survey, n=1250, the overall response rate was 10.9%, with a completion rate of 61.9%. Approximately 3 out of 4 adults reported that they avoided public places (888/1175, 75.6%), more than two-thirds avoided public transportation (808/1173, 68.9%), and 9 out of 10 practiced physical distancing (1046/1167, 89.7%). Approximately 1 out of 10 Sri Lankan persons reported being tested for COVID-19, and the majority of those received a polymerase chain reaction test (112/161, 70%). Significantly more males than females reported being tested for COVID-19 (98/554, 17.8% vs 61/578, 10.6%, respectively; P

The serial interval and effective reproduction number for coronavirus disease (COVID-19) are heterogenous, varying by demographic characteristics, region, and period. During February 1–July 13, 2020, we identified 4,080 transmission pairs in Georgia, USA, by using contact tracing information from COVID-19 cases reported to the Georgia Department of Public Health. We examined how various transmission characteristics were affected by symptoms, demographics, and period (during shelter-in-place and after subsequent reopening) and estimated the time course of reproduction numbers for all 159 Georgia counties. Transmission varied by time and place but also by persons’ sex and race. The mean serial interval decreased from 5.97 days in February–April to 4.40 days in June–July. Younger adults (20–50 years of age) were involved in most transmission events occurring during or after reopening. The shelter-in-place period was not long enough to prevent sustained virus transmission in densely populated urban areas connected by major transportation links.

BackgroundSouthern China is at risk for arborvirus disease transmission, including Zika virus and dengue. Patients often present to clinical care with non-specific acute febrile illnesses (AFI). To better describe the etiology of AFI, we implemented a two-year AFI surveillance project at five sentinel hospitals in Yunnan and Guangdong Provinces.MethodsBetween June 2017 and August 2019, we enrolled patients between 2 and 65 years of age presenting at one sentinel hospital in Mengla County, Yunnan, and four in Jiangmen City, Guangdong, with symptoms of AFI (acute onset of fever ≥ 37.5°C within the past 7 days) without respiratory symptoms or diarrhea. Demographic, epidemiologic, and clinical information was obtained and entered into a web-based AFI surveillance database. A custom TaqMan Array card (TAC) was used to test patients' whole blood specimens for 27 different pathogens using real-time polymerase chain reaction assays.ResultsDuring the two-year project period, 836 patients were enrolled; 443 patients from Mengla County and 393 patients from Jiangmen City. The median age was 33 years [range: 2-65], and most were hospitalized [641, 77%]. Of 796 patients with valid TAC results, 341 (43%) were positive for at least one of the 10 unique pathogens detected. This included 205 (26%) patients positive for dengue virus, 60 (8%) for Orientia tsutsugamushi, and 42 (5%) for Coxiella burnetii. Ten patients (1%) in Jiangmen City tested positive for malaria, 8 of whom reported recent travel outside of China. TAC results were negative for 455 (57%) patients. None of the patients had a positive TAC detection for Zika virus.ConclusionsThe project detected variability in the etiology of AFI in Southern China and highlighted the importance of differential diagnosis. Dengue, O. tsutsugamushi, and C. burnetii were the most frequently identified pathogens among enrolled AFI patients. As a non-notifiable disease, the frequent detection of C. burnetii is noteworthy and warrants additional investigation. The project provided a framework for routine surveillance for persons presenting with AFI.

Phages, such as those infecting Bacteroides spp., have been proven to be reliable indicators of human fecal contamination in microbial source tracking (MST) studies, and the efficacy of these MST markers found to vary geographically. This study reports the application and evaluation of candidate MST methods (phages infecting previously isolated B. fragilis strain GB-124, newly isolated Bacteroides strains (K10, K29, and K33) and recently isolated Kluyvera intermedia strain ASH-08), along with non-source specific somatic coliphages (SOMCPH infecting strain WG-5) and indicator bacteria (Escherichia coli) for identifying fecal contamination pathways in Kolkata, India. Source specificity of the phage-based methods was first tested using 60 known non-human fecal samples from common animals, before being evaluated with 56 known human samples (municipal sewage) collected during both the rainy and dry season. SOMCPH were present in 40-90% of samples from different animal species and in 100% of sewage samples. Phages infecting Bacteroides strain GB-124 were not detected from the majority (95%) of animal samples (except in three porcine samples) and were present in 93 and 71% of the sewage samples in the rainy and dry season (Mean = 1.42 and 1.83 log10PFU/100mL, respectively), though at lower levels than SOMCPH (Mean = 3.27 and 3.02 log10PFU/100mL, respectively). Phages infecting strain ASH-08 were detected in 89 and 96% of the sewage samples in the rainy and dry season, respectively, but were also present in all animal samples tested (except goats). Strains K10, K29, and K30 were not found to be useful MST markers due to low levels of phages and/or co-presence in non-human sources. GB-124 and SOMCPH were subsequently deployed within two low-income neighborhoods to determine the levels and origin of fecal contamination in 110 environmental samples. E. coli, SOMCPH, and phages of GB-124 were detected in 68, 42, and 28% of the samples, respectively. Analyses of 166 wastewater samples from shared community toilets and 21 samples from sewage pumping stations from the same districts showed that SOMCPH were present in 100% and GB-124 phages in 31% of shared toilet samples (Median = 5.59 and

Inadequate sanitation can lead to exposure to fecal contamination through multiple environmental pathways and can result in adverse health outcomes. By understanding the relative importance of multiple exposure pathways, sanitation interventions can be tailored to those pathways with greatest potential public health impact. The SaniPath Exposure Assessment Tool allows users to identify and quantify human exposure to fecal contamination in low-resource urban settings through a systematic yet customizable process. The Tool includes: a project management platform; mobile data collection and a data repository; protocols for primary data collection; and automated exposure assessment analysis. The data collection protocols detail the process of conducting behavioral surveys with households, school children, and community groups to quantify contact with fecal exposure pathways and of collecting and analyzing environmental samples for E. coli as an indicator of fecal contamination. Bayesian analyses are used to estimate the percentage of the population exposed and the mean dose of fecal exposure from microbiological and behavioral data. Fecal exposure from nine pathways (drinking water, bathing water, surface water, ocean water, open drains, floodwater, raw produce, street food, and public or shared toilets) can be compared through a common metric-estimated ingestion of E. coli units (MPN or CFU) per month. The Tool generates data visualizations and recommendations for interventions designed for both scientific and lay audiences. When piloted in Accra, Ghana, the results of the Tool were comparable with that of an in-depth study conducted in the same neighborhoods and highlighted consumption of raw produce as a dominant exposure pathway. The Tool has been deployed in nine cities to date, and the results are being used by local authorities to design and prioritize programming and policy. The SaniPath Tool is a novel approach to support public-health evidence-based decision-making for urban sanitation policies and investments.