Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

BACKGROUND: Detection of malaria parasitaemia in samples that are negative by rapid diagnostic tests (RDTs) requires resource-intensive molecular tools. While pooled testing using a two-step strategy provides a cost-saving alternative to the gold standard of individual sample testing, statistical adjustments are needed to improve accuracy of prevalence estimates for a single step pooled testing strategy. METHODS: A random sample of 4670 malaria RDT negative dried blood spot samples were selected from a mass testing and treatment trial in Asembo, Gem, and Karemo, western Kenya. Samples were tested for malaria individually and in pools of five, 934 pools, by one-step quantitative polymerase chain reaction (qPCR). Maximum likelihood approaches were used to estimate subpatent parasitaemia (RDT-negative, qPCR-positive) prevalence by pooling, assuming poolwise sensitivity and specificity was either 100% (strategy A) or imperfect (strategy B). To improve and illustrate the practicality of this estimation approach, a validation study was constructed from pools allocated at random into main (734 pools) and validation (200 pools) subsets. Prevalence was estimated using strategies A and B and an inverse-variance weighted estimator and estimates were weighted to account for differential sampling rates by area. RESULTS: The prevalence of subpatent parasitaemia was 14.5% (95% CI 13.6-15.3%) by individual qPCR, 9.5% (95% CI (8.5-10.5%) by strategy A, and 13.9% (95% CI 12.6-15.2%) by strategy B. In the validation study, the prevalence by individual qPCR was 13.5% (95% CI 12.4-14.7%) in the main subset, 8.9% (95% CI 7.9-9.9%) by strategy A, 11.4% (95% CI 9.9-12.9%) by strategy B, and 12.8% (95% CI 11.2-14.3%) using inverse-variance weighted estimator from poolwise validation. Pooling, including a 20% validation subset, reduced costs by 52% compared to individual testing. CONCLUSIONS: Compared to individual testing, a one-step pooled testing strategy with an internal validation subset can provide accurate prevalence estimates of PCR-positivity among RDT-negatives at a lower cost.

BACKGROUND: Simultaneous infection with multiple malaria parasite strains is common in high transmission areas. Quantifying the number of strains per host, or the multiplicity of infection (MOI), provides additional parasite indices for assessing transmission levels but it is challenging to measure accurately with current tools. This paper presents new laboratory and analytical methods for estimating the MOI of Plasmodium falciparum. METHODS: Based on 24 single nucleotide polymorphisms (SNPs) previously identified as stable, unlinked targets across 12 of the 14 chromosomes within P. falciparum genome, three multiplex PCRs of short target regions and subsequent next generation sequencing (NGS) of the amplicons were developed. A bioinformatics pipeline including B4Screening pathway removed spurious amplicons to ensure consistent frequency calls at each SNP location, compiled amplicons by SNP site diversity, and performed algorithmic haplotype and strain reconstruction. The pipeline was validated by 108 samples generated from cultured-laboratory strain mixtures in different proportions and concentrations, with and without pre-amplification, and using whole blood and dried blood spots (DBS). The pipeline was applied to 273 smear-positive samples from surveys conducted in western Kenya, then providing results into StrainRecon Thresholding for Infection Multiplicity (STIM), a novel MOI estimator. RESULTS: The 24 barcode SNPs were successfully identified uniformly across the 12 chromosomes of P. falciparum in a sample using the pipeline. Pre-amplification and parasite concentration, while non-linearly associated with SNP read depth, did not influence the SNP frequency calls. Based on consistent SNP frequency calls at targeted locations, the algorithmic strain reconstruction for each laboratory-mixed sample had 98.5% accuracy in dominant strains. STIM detected up to 5 strains in field samples from western Kenya and showed declining MOI over time (q < 0.02), from 4.32 strains per infected person in 1996 to 4.01, 3.56 and 3.35 in 2001, 2007 and 2012, and a reduction in the proportion of samples with 5 strains from 57% in 1996 to 18% in 2012. CONCLUSION: The combined approach of new multiplex PCRs and NGS, the unique bioinformatics pipeline and STIM could identify 24 barcode SNPs of P. falciparum correctly and consistently. The methodology could be applied to field samples to reliably measure temporal changes in MOI.

Objective: A growing body of research has investigated the human microbiota and pregnancy outcomes, especially preterm birth. Most studies of the prenatal microbiota have focused on the vagina, with fewer investigating other body sites during pregnancy. Although pregnancy involves profound hormonal, immunological and metabolic changes, few studies have investigated either shifts in microbiota composition across pregnancy at different body sites or variation in composition at any site that may be explained by maternal characteristics. The purpose of this study was to investigate: (1) the stability of the vaginal, oral, and gut microbiota from early (8-14 weeks) through later (24-30 weeks) pregnancy among African American women according to measures of socioeconomic status, accounting for prenatal antibiotic use; (2) whether measures of socioeconomic status are associated with changes in microbiota composition over pregnancy; and (3) whether exposure to prenatal antibiotics mediate any observed associations between measures of socioeconomic status and stability of the vaginal, oral, and gut microbiota across pregnancy. Methods: We used paired vaginal, oral, or gut samples available for 16S rRNA gene sequencing from two time points in pregnancy (8-14 and 24-30 weeks) to compare within-woman changes in measures of alpha diversity (Shannon and Chao1) and beta-diversity (Bray-Curtis dissimilarity) among pregnant African American women (n = 110). Multivariable linear regression was used to examine the effect of level of education and prenatal health insurance as explanatory variables for changes in diversity, considering antibiotic exposure as a mediator, adjusting for age, obstetrical history, and weeks between sampling. Results: For the oral and gut microbiota, there were no significant associations between measures of socioeconomic status or prenatal antibiotic use and change in Shannon or Chao1 diversity. For the vaginal microbiota, low level of education (high school or less) was associated with an increase in Shannon and Chao1 diversity over pregnancy, with minimal attenuation when controlling for prenatal antibiotic use. Conversely, for within-woman Bray-Curtis dissimilarity for early compared to later pregnancy, low level of education and prenatal antibiotics were associated with greater dissimilarity for the oral and gut sites, with minimal attenuation when controlling for prenatal antibiotics, and no difference in dissimilarity for the vaginal site. Conclusions: Measures of maternal socioeconomic status are variably associated with changes in diversity across pregnancy for the vaginal, oral, and gut microbiota, with minimal attenuation by prenatal antibiotic exposure. Studies that evaluate stability of the microbiota across pregnancy in association with health outcomes themselves associated with socioeconomic status (such as preterm birth) should incorporate measures of socioeconomic status to avoid finding spurious relationships.

BACKGROUND: Although malaria control intervention has greatly decreased malaria morbidity and mortality in many African countries, further decline in parasite prevalence has stagnated in western Kenya. In order to assess if malaria transmission reservoir is associated with this stagnation, submicroscopic infection and gametocyte carriage was estimated. Risk factors and associations between malaria control interventions and gametocyte carriage were further investigated in this study. METHODS: A total of 996 dried blood spot samples were used from two strata, all smear-positives (516 samples) and randomly selected smear-negatives (480 samples), from a community cross-sectional survey conducted at peak transmission season in 2012 in Siaya County, western Kenya. Plasmodium falciparum parasite presence and density were determined by stained blood smear and by 18S mRNA transcripts using nucleic acid sequence-based amplification assay (NASBA), gametocyte presence and density were determined by blood smear and by Pfs25 mRNA-NASBA, and gametocyte diversity by Pfg377 mRNA RT-PCR and RT-qPCR. RESULTS: Of the randomly selected smear-negative samples, 69.6 % (334/480) were positive by 18S-NASBA while 18S-NASBA detected 99.6 % (514/516) smear positive samples. Overall, 80.2 % of the weighted population was parasite positive by 18S-NASBA vs 30.6 % by smear diagnosis and 44.0 % of the weighted population was gametocyte positive by Pfs25-NASBA vs 2.6 % by smear diagnosis. Children 5-15 years old were more likely to be parasitaemic and gametocytaemic by NASBA than individuals >15 years old or children <5 years old while gametocyte density decreased with age. Anaemia and self-reported fever within the past 24 h were associated with increased odds of gametocytaemia. Fever was also positively associated with parasite density, but not with gametocyte density. Anti-malarial use within the past 2 weeks decreased the odds of gametocytaemia, but not the odds of parasitaemia. In contrast, recent anti-malarial use was associated with lowered parasite density, but not the gametocyte density. Use of ITNs was associated with lower odds for parasitaemia in part of the study area with a longer history of ITN interventions. In the same part of study area, the odds of having multiple gametocyte alleles were also lower in individuals using ITNs than in those not using ITNs and parasite density was positively associated with gametocyte diversity. CONCLUSION: A large proportion of submicroscopic parasites and gametocytes in western Kenya might contribute to the stagnation in malaria prevalence, suggesting that additional interventions targeting the infectious reservoir are needed. As school aged children and persons with anaemia and fever were major sources for gametocyte reservoir, these groups should be targeted for intervention and prevention to reduce malaria transmission. Anti-malarial use was associated with lower parasite density and odds of gametocytaemia, but not the gametocyte density, indicating a limitation of anti-malarial impact on the transmission reservoir. ITN use had a protective role against parasitaemia and gametocyte diversity in western Kenya.

The objective of this paper is to study shedding patterns of cows infected with Mycobacterium avium subsp. paratuberculosis (MAP). While multiple single farm studies of MAP dynamics were reported, there is not large scale meta-analysis of both natural and experimental infections. Large difference in shedding patterns between experimentally and naturally infected cows were observed. Experimental infections are thus probably driven by different pathological mechanisms. For further evaluations of shedding patterns only natural infections were used. Within such infections, the transition to high shedding was studied as a proxy to the development of a clinical disease. The majority of studied cows never developed high shedding levels. Those that do, typically never reduced their shedding level to low or no shedding. Cows that eventually became high shedders showed a pattern of continuous shedding. In contrast, cows with an intermittent shedding pattern had a low probability to ever become high shedders. In addition, cows that start shedding at a younger age (less than three years of age) have a lower hazard of becoming high shedders compared to cows starting to shed at an older age. These data suggest the presence of three categories of immune control. Cows that are intermittent shedders have the infection process under control (no progressive infection). Cows that start shedding persistently at a young age partially control the infection, but eventually will be high shedders (slow progressive infection), while cows that start shedding persistently at an older age cannot effectively control the infection and become high shedders rapidly.

BACKGROUND: Low malaria parasite densities in pregnancy are a diagnostic challenge. PCR provides high sensitivity and specificity in detecting low density of parasites, but cost and technical requirements limit its application in resources-limited settings. Pooling samples for PCR detection was explored to estimate prevalence of submicroscopic malaria infection in pregnant women at delivery. Previous work uses gold-standard based methods to calculate sensitivity and specificity of tests, creating a challenge when newer methodologies are substantially more sensitive than the gold standard. Thus prevalence was estimated using Bayesian latent class models (LCMs) in this study. METHODS: Nested PCR (nPCR) for the 18S rRNA gene subunit of Plasmodium falciparum was conducted to detect malaria infection in microscopy-negative Malawian women on IPTp. Two-step sample pooling used dried blood spot samples (DBSs) collected from placenta or periphery at delivery. Results from nPCR and histology as well as previously published data were used to construct LCMs to estimate assay sensitivity and specificity. Theoretical confidence intervals for prevalence of infection were calculated for two-step and one-step pooling strategies. RESULTS: Of 617 microscopy-negative Malawian women, 39 (6.3%) were identified as actively infected by histology while 52 (8.4%) were positive by nPCR. One hundred forty (22.7%) individuals had past infection assessed by histology. With histology as a reference, 72% of women in the active infection group, 7.1% in the past infection group and 3.2% in histology-negative group were nPCR positive. Using latent class models without a gold standard, histology had a median sensitivity of 49.7% and specificity of 97.6% for active infection while PCR had a median sensitivity of 96.0% and specificity of 99.1%. The true prevalence of active infection was estimated at 8.0% (CI: 5.8-10.5%) from PCR. PCR also had similar sensitivity for detecting either peripheral or placental malaria for submicroscopic infections. One-step pooling would give similar confidence intervals for pool sizes less than 20 while reducing the number of tests performed. CONCLUSIONS: Pooled nPCR testing was a sensitive and resource-efficient strategy and LCMs provided precise prevalence estimates of submicroscopic infections. Compared to two-step pooling, one-step pooling could provide similar prevalence estimates at population levels with many fewer tests required.

Mathematical models for infectious disease are often used to improve our understanding of infection biology or to evaluate the potential efficacy of intervention programs. Here, we develop a mathematical model that aims to describe infection dynamics of Mycobacterium avium subspecies paratuberculosis (MAP). The model was developed using current knowledge of infection biology and also includes some components of MAP infection dynamics that are currently still hypothetical. The objective was to show methods for parameter estimation of state transition models and to connect simulation models with detailed real life data. Thereby making model predictions and results of simulations more reflective and predictive of real world situations. Longitudinal field data from a large observational study are used to estimate parameter values. It is shown that precise data, including molecular diagnostics on the obtained MAP strains, results in more precise and realistic parameter estimates. It is argued that modeling of infection disease dynamics is of great value to understand the patho-biology, epidemiology and control of infectious diseases. The quality of conclusions drawn from model studies depend on two key issues; first, the quality of biology that has gone in the process of developing the model structure; second the quality of the data that go into the estimation of the parameters and the quality and quantity of the data that go into model validation. The more real world data that are used in the model building process, the more likely that modeling studies will provide novel, innovative and valid results.