Search

Many important questions in infectious disease epidemiology involve associations between covariates (e.g., age or vaccination status) and infectiousness or susceptibility. Because disease transmission produces dependent outcomes, these questions are difficult or impossible to address using standard regression models from biostatistics. Pairwise survival analysis handles dependent outcomes by calculating likelihoods in terms of contact interval distributions in ordered pairs of individuals. The contact interval in the ordered pairij$$ ij $$ is the time from the onset of infectiousness ini$$ i $$ to infectious contact fromi$$ i $$ toj$$ j $$, where an infectious contact is sufficient to infectj$$ j $$ if they are susceptible. Here, we introduce a pairwise accelerated failure time regression model for infectious disease transmission that allows the rate parameter of the contact interval distribution to depend on individual‐level infectiousness covariates fori$$ i $$, individual‐level susceptibility covariates forj$$ j $$, and pair‐level covariates (e.g., type of relationship). This model can simultaneously handle internal infections (caused by transmission between individuals under observation) and external infections (caused by environmental or community sources of infection). We show that this model produces consistent and asymptotically normal parameter estimates. In a simulation study, we evaluate bias and confidence interval coverage probabilities, explore the role of epidemiologic study design, and investigate the effects of model misspecification. We use this regression model to analyze household data from Los Angeles County during the 2009 influenza A (H1N1) pandemic, where we find that the ability to account for external sources of infection increases the statistical power to estimate the effect of antiviral prophylaxis. [ABSTRACT FROM AUTHOR]

Nipah virus spillovers via consumption of date palm sap in Bangladesh vary substantially between years and have been associated with lower winter temperatures and precipitation. However, the mechanisms driving the interannual variation and the influence of weather remain unexplained. Here we investigated the hypothesis that weather patterns change human sap consumption and explain interannual variation in observed spillovers. We analyzed responses from a nationally representative survey conducted in Bangladesh in 2013–2016 on household date palm sap consumption and weather data for each division of Bangladesh, using logistic regression to examine whether sap consumption is associated with weather variability. We found significant associations of lower minimum temperatures and precipitation with increased household sap consumption during the sap harvesting season. This relationship was largely similar within all months and divisions, and strong associations of temperature (χ2 (1, n = 5,027) = 7.74, p < 0.01) and, independently, precipitation (χ2 = 8.00, p < 0.01) remained strong after accounting for month, location, and annual sap season. Interannual variation in date palm sap consumption in Bangladesh is likely best explained by temperature and precipitation patterns, where colder, drier winter days pose a higher risk for Nipah virus spillover. The knowledge gained in this study may be valuable for targeting timing of future behavioral interventions against consumption of date palm sap in Bangladesh. [ABSTRACT FROM AUTHOR]

Background: Medication Regimen Complexity (MRC) refers to the combination of medication classes, dosages, and frequencies. The objective of this study was to examine the relationship between the scores of different MRC tools and the clinical outcomes. Methods: We conducted a retrospective cohort study at Roger William Medical Center, Providence, Rhode Island, which included 317 adult patients admitted to the intensive care unit (ICU) between 1 February 2020 and 30 August 2020. MRC was assessed using the MRC Index (MRCI) and MRC for the Intensive Care Unit (MRC-ICU). A multivariable logistic regression model was used to identify associations among MRC scores, clinical outcomes, and a logistic classifier to predict clinical outcomes. Results: Higher MRC scores were associated with increased mortality, a longer ICU length of stay (LOS), and the need for mechanical ventilation (MV). MRC-ICU scores at 24 h were significantly (p < 0.001) associated with increased ICU mortality, LOS, and MV, with ORs of 1.12 (95% CI: 1.06–1.19), 1.17 (1.1–1.24), and 1.21 (1.14–1.29), respectively. Mortality prediction was similar using both scoring tools (AUC: 0.88 [0.75–0.97] vs. 0.88 [0.76–0.97]. The model with 15 medication classes outperformed others in predicting the ICU LOS and the need for MV with AUCs of 0.82 (0.71–0.93) and 0.87 (0.77–0.96), respectively. Conclusion: Our results demonstrated that both MRC scores were associated with poorer clinical outcomes. The incorporation of MRC scores in real-time therapeutic decision making can aid clinicians to prescribe safer alternatives. [ABSTRACT FROM AUTHOR]

The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. Estimation of the SAR is an important part of understanding and controlling the transmission of infectious diseases. In practice, it is most often estimated using binomial models such as logistic regression, which implicitly attribute all secondary infections in a household to the primary case. In the simplest case, the number of secondary infections in a household with m susceptibles and a single primary case is modeled as a binomial(m, p) random variable where p is the SAR. Although it has long been understood that transmission within households is not binomial, it is thought that multiple generations of transmission can be neglected safely when p is small. We use probability generating functions and simulations to show that this is a mistake. The proportion of susceptible household members infected can be substantially larger than the SAR even when p is small. As a result, binomial estimates of the SAR are biased upward and their confidence intervals have poor coverage probabilities even if adjusted for clustering. Accurate point and interval estimates of the SAR can be obtained using longitudinal chain binomial models or pairwise survival analysis, which account for multiple generations of transmission within households, the ongoing risk of infection from outside the household, and incomplete follow-up. We illustrate the practical implications of these results in an analysis of household surveillance data collected by the Los Angeles County Department of Public Health during the 2009 influenza A (H1N1) pandemic. Author summary: The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. The most common statistical models used to estimate the SAR are binomial models such as logistic regression, which implicitly assume that all secondary infections in a household are infected by the primary case. Here, we use analytical calculations and simulations to show that estimation of the SAR must account for multiple generations of transmission within households. As an example, we show that binomial models and statistical models that account for multiple generations of within-household transmission reach different conclusions about the household SAR for 2009 influenza A (H1N1) in Los Angeles County, with the latter models fitting the data better. In an epidemic, accurate estimation of the SAR allows rigorous evaluation of the effectiveness of public health interventions such as social distancing, prophylaxis or treatment, and vaccination. [ABSTRACT FROM AUTHOR]

The originally published, uncorrected article and the republished, corrected article are provided here for reference. This article was republished on September 12, 2023 to add Yushuf Sharker as the eighth author. [Extracted from the article]

Congenital heart disease (CHD) remains a significant risk factor for neurologic injury because altered fetal hemodynamics may be unable to support typical brain development during critical periods of growth and maturation. The primary objective was to assess differences in the cerebral biochemical profile between healthy fetuses and fetuses with complex CHD and to relate these with infant outcomes. Pregnant participants underwent fetal magnetic resonance imaging with cerebral proton magnetic resonance spectroscopy acquisitions as part of a prospective observational study. Cerebral metabolites of N-acetyl aspartate, creatine, choline, myo-inositol, scyllo-inositol, lactate, and relevant ratios were quantified using LCModel. We acquired 503 proton magnetic resonance spectroscopy images (controls = 333; CHD = 170) from 333 participants (controls = 221; CHD = 112). Mean choline levels were higher in CHD compared with controls (CHD 2.47 IU [Institutional Units] ± 0.44 and Controls 2.35 IU ± 0.45; P = 0.02), whereas N-acetyl aspartate:choline ratios were lower among CHD fetuses compared with controls (CHD 1.34 ± 0.40 IU vs controls 1.44 ± 0.48 IU; P = 0.001). Cerebral lactate was detected in all cohorts but increased in fetuses with transposition of the great arteries and single-ventricle CHD (median: 1.63 [IQR: 0.56-3.27] in transposition of the great arteries and median: 1.28 [IQR: 0-2.42] in single-ventricle CHD) compared with 2-ventricle CHD (median: 0.79 [IQR: 0-1.45]). Cerebral lactate also was associated with increased odds of death before discharge (OR: 1.75; P = 0.04). CHD is associated with altered cerebral metabolites in utero, particularly in the third trimester period of pregnancy, which is characterized by exponential brain growth and maturation, and is associated with survival to hospital discharge. The long-term neurodevelopmental consequences of these findings warrant further study. [Display omitted] [ABSTRACT FROM AUTHOR]

Antibiotic resistance is a leading cause of hospitalization and death worldwide. Heavy metals such as arsenic have been shown to drive co-selection of antibiotic resistance, suggesting arsenic-contaminated drinking water is a risk factor for antibiotic resistance carriage. This study aimed to determine the prevalence and abundance of antibiotic-resistant Escherichia coli (AR-Ec) among people and drinking water in high (Hajiganj, >100 μg/L) and low arsenic-contaminated (Matlab, <20 μg/L) areas in Bangladesh. Drinking water and stool from mothers and their children (<1 year) were collected from 50 households per area. AR-Ec was detected via selective culture plating and isolates were tested for antibiotic resistance, arsenic resistance, and diarrheagenic genes by PCR. Whole-genome sequencing (WGS) analysis was done for 30 E. coli isolates from 10 households. Prevalence of AR-Ec was significantly higher in water in Hajiganj (48%) compared to water in Matlab (22%, p <0.05) and among children in Hajiganj (94%) compared to children in Matlab (76%, p <0.05), but not among mothers. A significantly higher proportion of E. coli isolates from Hajiganj were multidrug-resistant (83%) compared to isolates from Matlab (71%, p <0.05). Co-resistance to arsenic and multiple antibiotics (MAR index >0.2) was observed in a higher proportion of water (78%) and child stool (100%) isolates in Hajiganj than in water (57%) and children (89%) in Matlab (p <0.05). The odds of arsenic-resistant bacteria being resistant to third-generation cephalosporin antibiotics were higher compared to arsenic-sensitive bacteria (odds ratios, OR 1.2-7.0, p <0.01). WGS-based phylogenetic analysis of E. coli isolates did not reveal any clustering based on arsenic exposure and no significant difference in resistome was found among the isolates between the two areas. The positive association detected between arsenic exposure and antibiotic resistance carriage among children in arsenic-affected areas in Bangladesh is an important public health concern that warrants redoubling efforts to reduce arsenic exposure., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Amin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: We investigated a cluster of patients with encephalitis in the Manikgonj and Rajbari Districts of Bangladesh in February 2008 to determine the etiology and risk factors for disease., Methods: We classified persons as confirmed Nipah cases by the presence of immunoglobulin M antibodies against Nipah virus (NiV), or by the presence of NiV RNA or by isolation of NiV from cerebrospinal fluid or throat swabs who had onset of symptoms between February 6 and March 10, 2008. We classified persons as probable cases if they reported fever with convulsions or altered mental status, who resided in the outbreak areas during that period, and who died before serum samples were collected. For the case-control study, we compared both confirmed and probable Nipah case-patients to controls, who were free from illness during the reference period. We used motion-sensor-infrared cameras to observe bat's contact of date palm sap., Results: We identified four confirmed and six probable case-patients, nine (90%) of whom died. The median age of the cases was 10 years; eight were males. The outbreak occurred simultaneously in two communities that were 44 km apart and separated by a river. Drinking raw date palm sap 2-12 days before illness onset was the only risk factor most strongly associated with the illness (adjusted odds ratio 25, 95% confidence intervals 3.3-∞, p<0.001). Case-patients reported no history of physical contact with bats, though community members often reported seeing bats. Infrared camera photographs showed that Pteropus bats frequently visited date palm trees in those communities where sap was collected for human consumption., Conclusion: This is the second Nipah outbreak in Bangladesh where date palm sap has been implicated as the vehicle of transmission. Fresh date palm sap should not be drunk, unless effective steps have been taken to prevent bat access to the sap during collection.

In an earlier study in Karachi, Pakistan, households that received free soap and handwashing promotion for 9 months reported 53% less diarrhea than controls. Eighteen months after the intervention ended, these households were enrolled in a follow-up study to assess sustainability of handwashing behavior. Upon re-enrollment, mothers in households originally assigned to the intervention were 1.5 times more likely to have a place with soap and water to wash hands (79% versus 53%, P = 0.001) and when asked to wash hands were 2.2 times more likely to rub their hands together at least three times (50% versus 23%, P = 0.002) compared with controls. In the ensuing 14 months, former intervention households reported a similar proportion of person-days with diarrhea (1.59% versus 1.88%, P = 0.66) as controls. Although intervention households showed better handwashing technique after 2 years without intervention, their soap purchases and diarrhea experience was not significantly different from controls.