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The relationship between facility-based malaria test positivity rate and community-based parasite prevalence.

ABSTRACT: INTRODUCTION:Malaria surveillance is a key pillar in the control of malaria in Africa. The value of using routinely collected data from health facilities to define malaria risk at community levels remains poorly defined. METHODS:Four cross-sectional parasite prevalence surveys were undertaken among residents at 36 enumeration zones in Kilifi county on the Kenyan coast and temporally and spatially matched to fever surveillance at 6 health facilities serving the same communities over 12 months. The age-structured functional form of the relationship between test positivity rate (TPR) and community-based parasite prevalence (PR) was explored through the development of regression models fitted by alternating the linear, exponential and polynomial terms for PR. The predictive ranges of TPR were explored for PR endemicity risk groups of control programmatic value using cut-offs of low (PR <5%) and high (PR ? 30%) transmission intensity. RESULTS:Among 28,134 febrile patients encountered for malaria diagnostic testing in the health facilities, 12,143 (43.2%: 95% CI: 42.6%, 43.7%) were positive. The overall community PR was 9.9% (95% CI: 9.2%, 10.7%) among 6,479 participants tested for malaria. The polynomial model was the best fitting model for the data that described the algebraic relationship between TPR and PR. In this setting, a TPR of ? 49% in all age groups corresponded to an age-standardized PR of ? 30%, while a TPR of < 40% corresponded to an age-standardized PR of < 5%. CONCLUSION:A non-linear relationship was observed between the relative change in TPR and changes in the PR, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission. However, larger, more spatially diverse data series using routinely collected TPR data matched to community-based infection prevalence data are required to explore the more practical implications of using TPR as a replacement for community PR.

SUBMITTER: Kamau A

PROVIDER: S-EPMC7540858 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The relationship between facility-based malaria test positivity rate and community-based parasite prevalence.

Kamau Alice A Mtanje Grace G Mataza Christine C Malla Lucas L Bejon Philip P Snow Robert W RW

PloS one 20201007 10

<h4>Introduction</h4>Malaria surveillance is a key pillar in the control of malaria in Africa. The value of using routinely collected data from health facilities to define malaria risk at community levels remains poorly defined.<h4>Methods</h4>Four cross-sectional parasite prevalence surveys were undertaken among residents at 36 enumeration zones in Kilifi county on the Kenyan coast and temporally and spatially matched to fever surveillance at 6 health facilities serving the same communities ove ...[more]

PMID: 33027313

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Project description:BackgroundMalaria surveillance is critical for monitoring changes in malaria morbidity over time. National Malaria Control Programmes often rely on surrogate measures of malaria incidence, including the test positivity rate (TPR) and total laboratory confirmed cases of malaria (TCM), to monitor trends in malaria morbidity. However, there are limited data on the accuracy of TPR and TCM for predicting temporal changes in malaria incidence, especially in high burden settings.MethodsThis study leveraged data from 5 malaria reference centres (MRCs) located in high burden settings over a 15-month period from November 2018 through January 2020 as part of an enhanced health facility-based surveillance system established in Uganda. Individual level data were collected from all outpatients including demographics, laboratory test results, and village of residence. Estimates of malaria incidence were derived from catchment areas around the MRCs. Temporal relationships between monthly aggregate measures of TPR and TCM relative to estimates of malaria incidence were examined using linear and exponential regression models.ResultsA total of 149,739 outpatient visits to the 5 MRCs were recorded. Overall, malaria was suspected in 73.4% of visits, 99.1% of patients with suspected malaria received a diagnostic test, and 69.7% of those tested for malaria were positive. Temporal correlations between monthly measures of TPR and malaria incidence using linear and exponential regression models were relatively poor, with small changes in TPR frequently associated with large changes in malaria incidence. Linear regression models of temporal changes in TCM provided the most parsimonious and accurate predictor of changes in malaria incidence, with adjusted R2 values ranging from 0.81 to 0.98 across the 5 MRCs. However, the slope of the regression lines indicating the change in malaria incidence per unit change in TCM varied from 0.57 to 2.13 across the 5 MRCs, and when combining data across all 5 sites, the R2 value reduced to 0.38.ConclusionsIn high malaria burden areas of Uganda, site-specific temporal changes in TCM had a strong linear relationship with malaria incidence and were a more useful metric than TPR. However, caution should be taken when comparing changes in TCM across sites.

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.

Project description:BackgroundThe fecal immunochemical test (FIT) is commonly used for colorectal cancer (CRC) screening. Despite demographic variations in stool hemoglobin concentrations, few data exist regarding optimal positivity thresholds by age and sex.ObjectiveTo identify programmatic (multitest) FIT performance characteristics and optimal FIT quantitative hemoglobin positivity thresholds in a large, population-based, screening program.DesignRetrospective cohort study.SettingKaiser Permanente Northern and Southern California.ParticipantsAdults aged 50 to 75 years who were eligible for screening and had baseline quantitative FIT results (2013 to 2014) and 2 years of follow-up. Nearly two thirds (411 241) had FIT screening in the previous 2 years.MeasurementsFIT programmatic sensitivity for CRC and number of positive test results per cancer case detected, overall and by age and sex.ResultsOf 640 859 persons who completed a baseline FIT and were followed for 2 years, 481 817 (75%) had at least 1 additional FIT and 1245 (0.19%) received a CRC diagnosis. Cancer detection (programmatic sensitivity) increased at lower positivity thresholds, from 822 in 1245 (66.0%) at 30 µg/g to 925 (74.3%) at 20 µg/g and 987 (79.3%) at 10 µg/g; the number of positive test results per cancer case detected increased from 43 at 30 µg/g to 52 at 20 µg/g and 85 at 10 µg/g. Reducing the positivity threshold from 20 to 15 µg/g would detect 3% more cancer cases and require 23% more colonoscopies. At the conventional FIT threshold of 20 µg/g, programmatic sensitivity decreased with increasing age (79.0%, 73.4%, and 68.9% for ages 50 to 59, 60 to 69, and 70 to 75 years, respectively; P = 0.009) and was higher in men than women (77.0% vs. 70.6%; P = 0.011).LimitationInformation on advanced adenoma was lacking.ConclusionIncreased cancer detection at lower positivity thresholds is counterbalanced by substantial increases in positive tests. Tailored thresholds may provide screening benefits that are more equal among different demographic groups, depending on local resources.Primary funding sourceNational Cancer Institute.

Project description:Importance:Drug overdose deaths continue to increase, despite the leveling off of prescription opioid use and policy changes limiting opioid prescribing. Illicit fentanyl is the leading cause of drug overdose death, and it is important to characterize the emerging combination of other illicit drugs with fentanyl, which increases the risk of overdose. Objective:To determine whether rates of the combination of nonprescribed fentanyl with cocaine or methamphetamine have changed in urine drug test (UDT) results through time. Design, Setting, and Participants:This cross-sectional study of UDT results from January 1, 2013, through September 30, 2018, included patient specimens submitted for UDTs by health care professionals as part of routine care. Patients were selected from health care practices across the United States, including substance use disorder treatment centers, pain management practices, primary care practices, behavioral health practices, obstetrics and gynecology practices, and multispecialty groups. The UDT analysis used liquid chromatography-tandem mass spectrometry to detect benzoylecgonine (cocaine metabolite), methamphetamine, fentanyl, and norfentanyl. Specimens from individuals reported to have been prescribed fentanyl were excluded. A convenience sample approach was used to randomly select 1 million unique patient UDT specimens from Millennium Health's UDT database for further analysis. Each specimen had associated cocaine, methamphetamine, and fentanyl UDT results. Exposures:Medically necessary UDT to detect benzoylecgonine (cocaine metabolite), methamphetamine, fentanyl, and norfentanyl, ordered by a health care professional as part of routine patient care. Main Outcomes and Measures:Rates of nonprescribed fentanyl positivity among cocaine- or methamphetamine-positive UDT results, quantified through time. Results:In a sampling of 1 million unique patients' UDT specimens analyzed for cocaine and fentanyl (median [interquartile range] age, 44 [19-69] years; 55.0% women), positivity rates for nonprescribed fentanyl among the cocaine-positive results increased significantly, from 0.9% (n?=?84) (95% CI, 0.7%-1.1%) in 2013 to 17.6% (n?=?427) (95% CI, 16.1%-19.1%) in 2018, a 1850% increase (??=?0.78; z?=?9.45; P?<?.001). In the same sampling of 1 million specimens, positivity rates for nonprescribed fentanyl among the methamphetamine-positive results also increased significantly, from 0.9% (n?=?29) (95% CI, 0.6%-1.2%) in 2013 to 7.9% (n?=?344) (95% CI, 7.1%-8.7%) in 2018, a 798% increase (??=?0.72; z?=?8.75; P?<?.001). Conclusions and Relevance:An increasing number of UDT results positive for cocaine or methamphetamine were also positive for nonprescribed fentanyl. This provides additional insight into recently reported increases in cocaine- and methamphetamine-related overdoses. Stimulant users who may be opioid naive are at a heightened risk of overdose when exposed to fentanyl. Clinicians need to be aware that patients presenting for treatment of suspected drug overdose or substance use disorder may have been exposed, knowingly or unknowingly, to multiple substances, including the combination of stimulants and opioids.

Dataset Information

The relationship between facility-based malaria test positivity rate and community-based parasite prevalence.

Publications

The relationship between facility-based malaria test positivity rate and community-based parasite prevalence.

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