Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high.
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ABSTRACT:
SUBMITTER: Fernandez-Cassi X
PROVIDER: S-EPMC8126994 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Test positivity rate (TPR)-confirmed cases per 100 suspected cases tested, and test-confirmed malaria case rate (IR)-cases per 1,000 population, are common indicators used routinely for malaria surveillance. However, few studies have explored relationships between these indicators over time and space. We studied the relationship between these indicators in children aged < 11 years presenting with suspected malaria to the outpatient departments of level IV health centers in Nagongera, Kihihi, and Walukuba in Uganda from October 2011 to June 2016. We evaluated trends in indicators over time and space, and explored associations using multivariable regression models. Overall, 65,710 participants visited the three clinics. Pairwise comparisons of TPR and IR by month showed similar trends, particularly for TPRs < 50% and during low-transmission seasons, but by village, the relationship was complex. Village mean annual TPRs remained constant, whereas IRs drastically declined with increasing distance from the health center. Villages that were furthest away from the health centers (fourth quartile for distance) had significantly lower IRs than nearby villages (first quartile), with an incidence rate ratio of 0.40 in Nagongera (95% CI: 0.23-0.63; P = 0.001), 0.55 in Kihihi (0.40-0.75; P < 0.001), and 0.25 in Walukuba (0.12-0.51; P < 0.001). Regression analysis results emphasized a nonlinear (cubic) relationship between TPR and IR, after accounting for month, village, season, and demographic factors. Results show that the two indicators are highly relevant for monitoring malaria burden. However, interpretation differs with TPR primarily indicating demand for malaria treatment resources and IR indicating malaria risk among health facility catchment populations.
| S-EPMC6609187 | biostudies-literature
Project description:BackgroundHigh altitude settings in Eastern Africa have been reported to experience increased malaria burden due to vector habitat expansion. This study explored possible associations between malaria test positivity rates and its predictors including malaria control measures and meteorological factors at a high-altitude, low malaria transmission setting, south of Mount Kilimanjaro.MethodsMalaria cases reported at the Tanganyika Plantation Company (TPC) hospital's malaria registers, meteorological data recorded at TPC sugar factory and data on bed nets distributed in Lower Moshi from 2009 to 2018 were studied. Correlation between bed nets distributed and malaria test positivity rates were explored by using Pearson correlation analysis and the associations between malaria test positivity rates and demographic and meteorological variables were determined by logistic regression and negative binomial regression analyses, respectively.ResultsMalaria cases reported at TPC hospital ranged between 0.48 and 2.26% per year and increased slightly at the introduction of malaria rapid diagnostic tests. The risk of testing positive for malaria were significantly highest among individuals aged between 6 and 15 years (OR = 1.65; 1.65 CI = 1.28-2.13; p = 0.001) and 16-30 years (OR = 1.49; CI = 1.17-1.89; p = 0.001) and when adjusted for age, the risk were significantly higher among male individuals when compared to female individuals (OR = 1.54; 1.00-1.31; p = 0.044). Malaria test positivity rates were positively associated with average monthly minimum temperatures and negatively associated with average monthly maximum temperatures (incidence rate ratio (IRR) = 1.37, 95% confidence interval (CI) = 1.05-1.78, p = 0.019 and IRR = 0.72, 95% CI = 0.58-0.91, p = 0.005, respectively). When analysed with one month lag for predictor variables, malaria test positivity rates were still significantly associated with average monthly minimum and maximum temperatures (IRR = 1.67, 95% CI = 1.28-2.19, p = 0.001 and IRR = 0.68, 95% CI = 0.54-0.85, p = 0.001, respectively). Average monthly rainfall and relative humidity with or without a one month lag was not associated with malaria test positivity rates in the adjusted models. Explopring possible associations between distribution of long-lasting insecticidal nets, (LLINs) and malaria test positivity rates showed no apparent correlation between numbers of LLINs distributed in a particular year and malaria test positivity rates.ConclusionIn Lower Moshi, the risk of being tested positive for malaria was highest for older children and male individuals. Higher minimum and lower maximum temperatures were the strongest climatic predictors for malaria test positivity rates. In areas with extensive irrigation activity as in Lower Moshi, vector abundance and thus malaria transmission may be less dependent on rainfall patterns and humidity. Mass distribution of LLINs did not have an effect in this area with already very low malaria transmission.
| S-EPMC8056660 | biostudies-literature
Project description:Detection and isolation of infected people are believed to play an important role in the control of the COVID-19 pandemic. Some countries conduct large-scale screenings for testing, whereas others test mainly people with high prior probability of infection such as showing severe symptoms and/or having an epidemiological link with a known or suspected case or cluster of cases. However, what a good testing strategy is and whether the difference in testing strategy shows a meaningful, measurable impact on the COVID-19 epidemic remain unknown. Here, we showed that patterns of association between effective reproduction number (Rt) and test positivity rate can illuminate differences in testing situation among different areas, using global and local data from Japan. This association can also evaluate the adequacy of current testing systems and what information is captured in COVID-19 surveillance. The differences in testing systems alone cannot predict the results of epidemic containment efforts. Furthermore, monitoring test positivity rates and severe case proportions among the nonelderly can predict imminent case count increases. Monitoring test positivity rates in conjunction with the concurrent Rt could be useful to assess and strengthen public health management and testing systems and deepen understanding of COVID-19 epidemic dynamics.
| S-EPMC8125747 | biostudies-literature
Project description:BackgroundThe test positivity rate (TPR), defined as the number of laboratory-confirmed malaria tests per 100 suspected cases examined, is widely used by malaria surveillance programs as one of several key indicators of temporal trends in malaria incidence. However, there have been few studies using empiric data to examine the quantitative nature of this relationship.MethodsTo characterize the relationship between the test positivity rate and the incidence of malaria, we fit regression models using the confirmed malaria case rate as the outcome of interest and TPR as the predictor of interest. We varied the relationship between the two by alternating linear and polynomial terms for TPR, and compared the goodness of fit of each model.ResultsA total of 7,668 encounters for malaria diagnostic testing were recorded over the study period within a catchment area of 25,617 persons. The semi-annual TPR ranged from 4.5% to 59% and the case rates ranged from 0.5 to 560 per 1,000 persons. The best fitting model was an exponential growth model (R2 = 0.80, AIC = 637). At low transmission levels (TPR<10%), the correlation between TPR and CMCR was poor, with large reductions in the TPR, for example from 10% to 1%, was associated with a minimal change in the CMCR (3.9 to 1.7 cases per 1,000 persons). At higher transmission levels, the exponential relationship made relatively small changes in TPR suggestive of sizeable change in estimated malaria incidence, suggesting that TPR remains a valuable surveillance indicator in such settings.ConclusionsThe TPR and the confirmed malaria case rate have a non-linear relationship, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission.
| S-EPMC4809590 | biostudies-literature
Project description:BackgroundThe public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems. The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19. We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data.MethodsUsing county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties, we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29, 2020 to June 30, 2022. We included covariates such as COVID-19 vaccine coverage in the county, comorbidities, demographic variables, and holiday gatherings.FindingsWastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission. Models that included wastewater had higher predictive power than models that included clinical cases only, increasing the accuracy of the model by 15%. Predicted hospital admissions correlated highly with observed admissions (r = 0.77) with an average difference of 0.013 hospitalizations per 100,000 (95% CI = [0.002, 0.025]).InterpretationUsing wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone. The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.
| S-EPMC10665827 | biostudies-literature
Project description:Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses and vaccination coverage needed to address the ongoing spread of COVID-19 in each United States (U.S.) state. However, reliable, timely data based on representative population sampling are unavailable, and reported case and test positivity rates are highly biased. A simple data-driven Bayesian semi-empirical modeling framework was developed and used to evaluate state-level prevalence and seroprevalence of COVID-19 using daily reported cases and test positivity ratios. The model was calibrated to and validated using published state-wide seroprevalence data, and further compared against two independent data-driven mathematical models. The prevalence of undiagnosed COVID-19 infections is found to be well-approximated by a geometrically weighted average of the positivity rate and the reported case rate. Our model accurately fits state-level seroprevalence data from across the U.S. Prevalence estimates of our semi-empirical model compare favorably to those from two data-driven epidemiological models. As of December 31, 2020, we estimate nation-wide a prevalence of 1.4% [Credible Interval (CrI): 1.0%-1.9%] and a seroprevalence of 13.2% [CrI: 12.3%-14.2%], with state-level prevalence ranging from 0.2% [CrI: 0.1%-0.3%] in Hawaii to 2.8% [CrI: 1.8%-4.1%] in Tennessee, and seroprevalence from 1.5% [CrI: 1.2%-2.0%] in Vermont to 23% [CrI: 20%-28%] in New York. Cumulatively, reported cases correspond to only one third of actual infections. The use of this simple and easy-to-communicate approach to estimating COVID-19 prevalence and seroprevalence will improve the ability to make public health decisions that effectively respond to the ongoing COVID-19 pandemic.
| S-EPMC8448371 | biostudies-literature
Project description:Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) wastewater-based epidemiology (WBE) has been applied as a complementary approach for spatial tracking of coronavirus disease 2019 cases (COVID-19) as well as early warning of the occurrence of infected populations. The present study presents the result of the monitoring of sanitary sewerage in the municipality of Niterói, a metropolitan region of Rio de Janeiro (Brazil) and its use as a complementary indicator in the surveillance of COVID-19 cases, thus assisting actions of public health from local authorities. Twelve composite raw sewage samples were weekly collected from two wastewater treatment plants (WWTPs) and alternately from 17 sewer pipes (SP) from surrounding neighbourhoods and slums throughout 20 weeks (April 15th to August 25th, 2020). Two hundred twenty-three samples were concentrated using the ultracentrifugation-based method and SARS-CoV-2 RNA detected and quantified by RT-qPCR using primers and probe targeting the N2 genome. SARS-CoV-2 RNA was detected in 84.3% (188/223) of samples with a positive rate ranging from 42% (5/12) in the first week of monitoring to 100% during the peak of epidemic with viral concentration ranging from 3.1 to 7.1 log10 genome copies /100 mL throughout the studied period. Positive rates were higher in WWTPs when compared to SP, being useful tool for monitoring trends in the evolution of the COVID-19 curve, while SP data were more effective when health public interventions were needed. Whole-genome sequencing using Illumina MiSeq System confirmed the lineage of three genomes as B.1.1.33 (clade G) containing the nucleotide substitutions observed in strains that circulate in the Rio de Janeiro during the period of this study. In addition, geoprocessing tool was used to build heat maps based on SARS-CoV-2 data from sewage samples, which were weekly updated and available online to the general population as an indicator of the ongoing epidemic situation in Niterói city, raising public awareness.
| S-EPMC7832254 | biostudies-literature
Project description:Objectives. We wished to determine test re-test reliability and construct validity of the star-track test of manual dexterity. Design. Test re-test reliability was examined in a controlled study. Construct validity was tested in a blinded randomized crossover study. Setting. The study was performed at a university hospital in Denmark. Participants. A total of 11 subjects for test re-test and 20 subjects for the construct validity study were included. All subjects were healthy volunteers. Intervention. The test re-test trial had two measurements with 2 days pause in between. The interventions in the construct validity study included baseline measurement, intervention 1: fatigue, intervention 2: stress, and intervention 3: fatigue and stress. There was a 2 day pause between each intervention. Main outcome measure. An integrated measure of completion time and number of errors was used. Results. All participants completed the study (test re-test n = 11; construct validity n = 20). The test re-testshowed a strong Pearson product-moment correlation (r = 0.90, n = 11, P < 0.01) with no sign of learning effect. The 20 subjects in the construct validity trial were randomized to the order of the four interventions, so that all subjects completed each intervention once. A repeated measures ANOVA determined that mean integrated measure differed between interventions (p = 0.002). Post hoc tests using Bonferroni correction revealed that compared with baseline all interventions had significantly higher integrated scores ranging from 47-59% difference in mean. Conclusion. The star track test of manual dexterity had a strong test re-test reliability, and was able to discriminate between a subject's normal manual dexterity and dexterity after exposure to fatigue and/or stress.
| S-EPMC4411521 | biostudies-literature
Project description:Importance:The ability to predict the pathology underlying different neurodegenerative syndromes is of critical importance owing to the advent of molecule-specific therapies. Objective:To determine the rates of positron emission tomography (PET) amyloid positivity in the main clinical variants of primary progressive aphasia (PPA). Design, Setting, and Participants:This prospective clinical-pathologic case series was conducted at a tertiary research clinic specialized in cognitive disorders. Patients were evaluated as part of a prospective, longitudinal research study between January 2002 and December 2015. Inclusion criteria included clinical diagnosis of PPA; availability of complete speech, language, and cognitive testing; magnetic resonance imaging performed within 6 months of the cognitive evaluation; and PET carbon 11-labeled Pittsburgh Compound-B or florbetapir F 18 brain scan results. Of 109 patients referred for evaluation of language symptoms who underwent amyloid brain imaging, 3 were excluded because of incomplete language evaluations, 5 for absence of significant aphasia, and 12 for presenting with significant initial symptoms outside of the language domain, leaving a cohort of 89 patients with PPA. Main Outcomes and Measures:Clinical, cognitive, neuroimaging, and pathology results. Results:Twenty-eight cases were classified as imaging-supported semantic variant PPA (11 women [39.3%]; mean [SD] age, 64 [7] years), 31 nonfluent/agrammatic variant PPA (22 women [71.0%]; mean [SD] age, 68 [7] years), 26 logopenic variant PPA (17 women [65.4%]; mean [SD] age, 63 [8] years), and 4 mixed PPA cases. Twenty-four of 28 patients with semantic variant PPA (86%) and 28 of 31 patients with nonfluent/agrammatic variant PPA (90%) had negative amyloid PET scan results, while 25 of 26 patients with logopenic variant PPA (96%) and 3 of 4 mixed PPA cases (75%) had positive scan results. The amyloid positive semantic variant PPA and nonfluent/agrammatic variant PPA cases with available autopsy data (2 of 4 and 2 of 3, respectively) all had a primary frontotemporal lobar degeneration and secondary Alzheimer disease pathologic diagnoses, whereas autopsy of 2 patients with amyloid PET-positive logopenic variant PPA confirmed Alzheimer disease. One mixed PPA patient with a negative amyloid PET scan had Pick disease at autopsy. Conclusions and Relevance:Primary progressive aphasia variant diagnosis according to the current classification scheme is associated with Alzheimer disease biomarker status, with the logopenic variant being associated with carbon 11-labeled Pittsburgh Compound-B positivity in more than 95% of cases. Furthermore, in the presence of a clinical syndrome highly predictive of frontotemporal lobar degeneration pathology, biomarker positivity for Alzheimer disease may be associated more with mixed pathology rather than primary Alzheimer disease.
| S-EPMC5885868 | biostudies-literature
Project description:PURPOSE: To assess the ability of patients to predict the need for retreatment with intravitreal ranibizumab in neovascular age-related macular degeneration (NVAMD) based on their perception of visual deterioration or distortion of objects in their everyday environment (environmental Amsler). METHODS: A questionnaire was given to 89 patients undergoing optical coherence tomography (OCT)-guided retreatment with intravitreal ranibizumab for NVAMD following an initial loading regimen of three injections and with at least 12-month follow-up. The patient's opinion on the need for an injection on the current visit, based on their perception of change in environmental Amsler, was recorded. This subjective measure was compared with the objective evaluation of retreatment, based on predefined retreatment criteria comprising of changes in visual acuity and morphological changes on OCT. The patients were then instructed on the technique of environmental Amsler, and this evaluation was repeated. The sensitivity and specificity of patient prediction were analyzed at baseline and after the training. RESULTS: The ability of patients to predict disease activity at baseline showed a sensitivity of 61% and specificity of 96.6%. The area under the receiver operating characteristic curve was 0.8. The presence of macular fluid correlated well with the patient's perception of an abnormal environmental Amsler. After training, the sensitivity and specificity improved to 87.5% and 98.5%, respectively. CONCLUSION: In real life, most patients are able to predict the reactivation of the disease in NVAMD, after 12-month follow-up, after training to monitor their symptoms using the environmental Amsler test.
| S-EPMC3298986 | biostudies-other