Search

Summary: Background: The standard malaria rapid diagnostic test (RDT) and newer ultra-sensitive RDT (uRDT) target Plasmodium falciparum histidine rich protein-2 (HRP2), which persists post-treatment. The duration of test positivity has not previously been studied in a low transmission setting. Methods: We conducted a longitudinal cohort study in a low transmission setting in Namibia. RDT-positive individuals identified through passive and active case detection were treated and followed weekly for testing by RDT and uRDT, HRP2 quantification, quantitative PCR (qPCR) of parasitemia, and quantitative reverse transcriptase PCR (RT-PCR) of gametocytemia, until RDT and uRDT were negative for two consecutive weeks. Determinants of persistent positivity were identified using Cox proportional hazards models. Findings: Among 137 participants with complete follow-up and no evidence of resurgence during follow-up, median duration of positivity was 42 days (range: 3−98 range) for RDT, compared to 67 days (range 12–105) for uRDT. In a sub-analysis of those with laboratory data before treatment (n = 60), drug resistance did not explain persistent positivity. Younger age (

Abstract Background In 2020, the Zambia National Malaria Elimination Centre targeted the distribution of long-lasting insecticidal nets (LLINs) and indoor-residual spraying (IRS) campaigns based on sub-district micro-planning, where specified geographical areas at the health facility catchment level were assigned to receive either LLINs or IRS. Using data from the 2021 Malaria Indicator Survey (MIS), the objectives of this analysis were to (1) assess how well the micro-planning was followed in distributing LLINs and IRS, (2) investigate factors that contributed to whether households received what was planned, and (3) investigate how overall coverage observed in the 2021 MIS compared to the 2018 MIS conducted prior to micro-planning. Methods Households’ receipt of ≥ 1 LLIN, and/or IRS within the past 12 months in the 2021 MIS, was compared against the micro-planning area under which the households fell. GPS points for 3,550 households were overlayed onto digitized micro-planning maps in order to determine what micro-plan the households fell under, and thus whether they received their planned intervention. Mixed-effects regression models were conducted to investigate what factors affected whether these households: (1) received their planned intervention, and (2) received any intervention. Finally, coverage indicators between the 2021 and 2018 MIS were compared. Results Overall, 60.0% (95%CI 55.4, 64.4) of households under a micro-plan received their assigned intervention, with significantly higher coverage of the planned intervention in LLIN-assigned areas (75.7% [95%CI 69.5, 80.9]) compared to IRS-assigned areas (49.4% [95%CI: 44.4, 54.4]). Regression analysis indicated that households falling under the IRS micro-plan had significantly reduced odds of receiving their planned intervention (OR: 0.34 [95%CI 0.24, 0.48]), and significantly reduced odds of receiving any intervention (OR: 0.51 [95%CI 0.37, 0.72] ), compared to households under the LLIN micro-plan. Comparison between the 2021 and 2018 MIS indicated a 27% reduction in LLIN coverage nationally in 2021, while IRS coverage was similar. Additionally, between 2018 and 2021, there was a 13% increase in households that received neither intervention. Conclusions This analysis shows that although the micro-planning strategy adopted in 2020 worked much better for LLIN-assigned areas compared to IRS-assigned areas, there was reduced overall vector control coverage in 2021 compared to 2018 before micro-planning.

Abstract Background Community case management of malaria (CCM) has been expanded in many settings, but there are limited data describing the impact of these services in routine implementation settings or at large scale. Zambia has intensively expanded CCM since 2013, whereby trained volunteer community health workers (CHW) use rapid diagnostic tests and artemether-lumefantrine to diagnose and treat uncomplicated malaria. Methods This retrospective, observational study explored associations between changing malaria service point (health facility or CHW) density per 1000 people and severe malaria admissions or malaria inpatient deaths by district and month in a dose–response approach, using existing routine and programmatic data. Negative binomial generalized linear mixed-effect models were used to assess the impact of increasing one additional malaria service point per 1000 population, and of achieving Zambia’s interim target of 1 service point per 750 population. Access to insecticide-treated nets, indoor-residual spraying, and rainfall anomaly were included in models to reduce potential confounding. Results The study captured 310,855 malaria admissions and 7158 inpatient malaria deaths over 83 districts (seven provinces) from January 2015 to May 2020. Total CHWs increased from 43 to 4503 during the study period, while health facilities increased from 1263 to 1765. After accounting for covariates, an increase of one malaria service point per 1000 was associated with a 19% reduction in severe malaria admissions among children under five (incidence rate ratio [IRR] 0.81, 95% confidence interval [CI] 0.75–0.87, p

Introduction As malaria declines, innovative tools are required to further reduce transmission and achieve elimination. Mass drug administration (MDA) of artemisinin-based combination therapy (ACT) is capable of reducing malaria transmission where coverage of control interventions is already high, though the impact is short-lived. Combining ACT with ivermectin, an oral endectocide shown to reduce vector survival, may increase its impact, while also treating ivermectin-sensitive co-endemic diseases and minimising the potential impact of ACT resistance in this context.Methods and analysis MATAMAL is a cluster-randomised placebo-controlled trial. The trial is being conducted in 24 clusters on the Bijagós Archipelago, Guinea-Bissau, where the peak prevalence of Plasmodium falciparum (Pf) parasitaemia is approximately 15%. Clusters have been randomly allocated to receive MDA with dihydroartemisinin–piperaquine and either ivermectin or placebo. The primary objective is to determine whether the addition of ivermectin MDA is more effective than dihydroartemisinin–piperaquine MDA alone in reducing the prevalence of P. falciparum parasitaemia, measured during peak transmission season after 2 years of seasonal MDA. Secondary objectives include assessing prevalence after 1 year of MDA; malaria incidence monitored through active and passive surveillance; age-adjusted prevalence of serological markers indicating exposure to P. falciparum and anopheline mosquitoes; vector parous rates, species composition, population density and sporozoite rates; prevalence of vector pyrethroid resistance; prevalence of artemisinin resistance in P. falciparum using genomic markers; ivermectin’s impact on co-endemic diseases; coverage estimates; and the safety of combined MDA.Ethics and dissemination The trial has been approved by the London School of Hygiene and Tropical Medicine’s Ethics Committee (UK) (19156) and the Comite Nacional de Eticas de Saude (Guinea-Bissau) (084/CNES/INASA/2020). Results will be disseminated in peer-reviewed publications and in discussion with the Bissau-Guinean Ministry of Public Health and participating communities.Trial registration number NCT04844905.

ABSTRACT Rapid diagnostic tests (RDTs) that detect antigen indicative of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can help in making quick health care decisions and regularly monitoring groups at risk of infection. With many RDT products entering the market, it is important to rapidly evaluate their relative performance. Comparison of clinical evaluation study results is challenged by protocol design variations and study populations. Laboratory assays were developed to quantify nucleocapsid (N) and spike (S) SARS-CoV-2 antigens. Quantification of the two antigens in nasal eluates confirmed higher abundance of N than S antigen. The median concentration of N antigen was 10 times greater than S per genome equivalent. The N antigen assay was used in combination with quantitative reverse transcription (RT)-PCR to qualify a panel composed of recombinant antigens, inactivated virus, and clinical specimen pools. This benchmarking panel was applied to evaluate the analytical performance of the SD Biosensor Standard Q COVID-19 antigen (Ag) test, Abbott Panbio COVID-19 Ag rapid test, Abbott BinaxNOW COVID-19 Ag test, and the LumiraDx SARS-CoV-2 Ag test. The four tests displayed different sensitivities toward the different panel members, but all performed best with the clinical specimen pool. The concentration for a 90% probability of detection across the four tests ranged from 21 to 102 pg/mL of N antigen in the extracted sample. Benchmarking panels provide a quick way to verify the baseline performance of a diagnostic and enable direct comparisons between diagnostic tests. IMPORTANCE This study reports the results for severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) nucleocapsid (N) and spike (S) antigen quantification assays and their performance against clinical reverse transcription (RT)-PCR results, thus describing an open-access quantification method for two important SARS-CoV-2 protein analytes. Characterized N antigen panels were used to evaluate the limits of detection of four different rapid tests for SARS-CoV-2 against multiple sources of nucleocapsid antigen, demonstrating proof-of-concept materials and methodology to evaluate SARS-CoV-2 rapid antigen detection tests. Quantification of N antigen was used to characterize the relationship between viral count and antigen concentration among clinical samples and panel members of both clinical sample and viral culture origin. This contributes to a deeper understanding of protein antigen and molecular analytes and presents analytical methods complementary to clinical evaluation for characterizing the performance of both laboratory-based and point-of-care rapid diagnostics for SARS-CoV-2.

The relationship between N-antigen concentration and viral load within and across different specimens guides the clinical performance of rapid diagnostic tests (RDT) in different uses. A prospective study was conducted in Porto Velho, Brazil, to investigate RDT performance in different specimen types as a function of the correlation between antigen concentration and viral load. The study included 214 close contacts with recent exposures to confirmed cases, aged 12 years and older and with various levels of vaccination. Antigen concentration was measured in nasopharyngeal swab (NPS), anterior nares swab (ANS), and saliva specimens. Reverse transcriptase (RT)-PCR was conducted on the NPS and saliva specimens, and two RDTs were conducted on ANS and one RDT on saliva. Antigen concentration correlated well with viral load when measured in the same specimen type but not across specimen types. Antigen levels were higher in symptomatic cases compared to asymptomatic/oligosymptomatic cases and lower in saliva compared to NPS and ANS samples. Discordant results between the RDTs conducted on ANS and the RT-PCR on NPS were resolved by antigen concentration values. The analytical limit-of-detection of RDTs can be used to predict the performance of the tests in populations for which the antigen concentration is known. The antigen dynamics across different sample types observed in SARS-CoV-2 disease progression support use of RDTs with nasal samples. Given lower antigen concentrations in saliva, rapid testing using saliva is expected to require improved RDT analytical sensitivity to achieve clinical sensitivity similar to rapid testing of nasal samples.

Plasmodium falciparum infection in pregnancy is a major cause of adverse pregnancy outcomes. Here, the authors combine performance estimates of standard rapid diagnostic tests with modelling to assess whether screening at antenatal visits improves upon current intermittent preventative therapy.

Abstract Background The Gambia has successfully reduced malaria transmission. The human reservoir of infection could further decrease if malaria-infected individuals could be identified by highly sensitive, field-based, diagnostic tools and then treated. Methods A cross-sectional survey was done at the peak of the 2017 malaria season in 47 Gambian villages. From each village, 100 residents were randomly selected for finger-prick blood samples to detect Plasmodium falciparum infections using highly sensitive rapid diagnostic tests (HS-RDT) and PCR. The sensitivity and specificity of the HS-RDT were estimated (assuming PCR as the gold standard) across varying transmission intensities and in different age groups. A deterministic, age-structured, dynamic model of malaria transmission was used to estimate the impact of mass testing and treatment (MTAT) with HS-RDT in four different scenarios of malaria prevalence by PCR: 5, 15, 30, and 60%, and with seasonal transmission. The impact was compared both to MTAT with conventional RDT and mass drug administration (MDA). Results Malaria prevalence by HS-RDT was 15% (570/3798; 95% CI 13.9–16.1). The HS-RDT sensitivity and specificity were 38.4% (191/497, 95% CI 34.2–42.71) and 88.5% (2922/3301; 95% CI 87.4–89.6), respectively. Sensitivity was the highest (50.9%, 95% CI 43.3–58.5%) in high prevalence villages (20–50% by PCR). The model predicted that in very low transmission areas (≤ 5%), three monthly rounds of MTAT with HS-RDT, starting towards the end of the dry season and testing 65 or 85% of the population for 2 consecutive years, would avert 62 or 78% of malaria cases (over 2 years), respectively. The effect of the intervention would be lower in a moderate transmission setting. In all settings, MDA would be superior to MTAT with HS-RDT which would be superior to MTAT with conventional RDT. Conclusion The HS-RDT’s field sensitivity was modest and varied by transmission intensity. In low to very low transmission areas, three monthly rounds per year of MTAT with HS-RDT at 85% coverage for 2 consecutive years would reduce malaria prevalence to such low levels that additional strategies may achieve elimination. The model prediction would need to be confirmed by cluster-randomized trials.

Abstract Reaching the overall goal of eliminating malaria requires halting disease transmission. One approach to blocking transmission is to prevent passage of the parasite to a mosquito, by preventing formation or transmission of gametocytes. An alternative approach, pioneered in the veterinary field, is to use endectocides, which are molecules that render vertebrate blood meals toxic for the mosquito vector, also killing the parasite. Field studies and modelling suggest that reducing the lifespan of the mosquito may significantly reduce transmission, given the lengthy maturation process of the parasite. To guide the development of new endectocides, or the reformulation of existing molecules, it is important to construct a framework of the required attributes, commonly called the target candidate profile. Here, using a combination of insights from current endectocides, mathematical models of the malaria transmission dynamics, and known impacts of vector control, a target candidate profile (TCP-6) and a regulatory strategy are proposed for a transmission reducing agent. The parameters chosen can be used to assess the potential of a new medicine, independent of whether it has classical endectocide activity, reduces the insect and parasite lifespan or any combination of all three, thereby constituting an ‘endectocidal transmission blocking’ paradigm.

Abstract Background Mosquitoes that feed on animals can survive and mediate residual transmission of malaria even after most humans have been protected with insecticidal bednets or indoor residual sprays. Ivermectin is a widely-used drug for treating parasites of humans and animals that is also insecticidal, killing mosquitoes that feed on treated subjects. Mass administration of ivermectin to livestock could be particularly useful for tackling residual malaria transmission by zoophagic vectors that evade human-centred approaches. Ivermectin comes from a different chemical class to active ingredients currently used to treat bednets or spray houses, so it also has potential for mitigating against emergence of insecticide resistance. However, the duration of insecticidal activity obtained with ivermectin is critical to its effectiveness and affordability. Results A slow-release formulation for ivermectin was implanted into cattle, causing 40 weeks of increased mortality among Anopheles arabiensis that fed on them. For this zoophagic vector of residual malaria transmission across much of Africa, the proportion surviving three days after feeding (typical mean duration of a gonotrophic cycle in field populations) was approximately halved for 25 weeks. Conclusions This implantable ivermectin formulation delivers stable and sustained insecticidal activity for approximately 6 months. Residual malaria transmission by zoophagic vectors could be suppressed by targeting livestock with this long-lasting formulation, which would be impractical or unacceptable for mass treatment of human populations.

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection.

Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.