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Background: Wildfires are thought to become more prevalent during periods of extended dry weather. This issue is examined using two dryness metrics commonly applied in Australian fire management agencies. Aims: This paper investigated links between wildfire incidence and the Keetch–Byram Drought Index (KBDI) and McArthur's Drought Factor (DF) across the state of Victoria, Australia. Methods: Weather records and data from 41 418 wildfires that occurred across the State over a 17-year period were compiled to examine the distributions of KBDI and DF on days with fires smaller and larger than 5 ha in area and all days, using kernel density plots. Key results: Days with fires, particularly days with fires that escaped initial attack, have higher DFs and KBDIs compared with all days. These differences vary between regions and are greatest in areas with moist climates. Conclusions and implications: An appreciation of dryness conditions using tools such as KBDI and DF is useful for understanding fire potential, particularly in areas that experience higher and more regular rainfall. McArthur's Drought Factor and the Keetch–Byram Drought Index are higher than normal on days with fires in Victoria, Australia. These metrics provide a more reliable indication of fire potential in high-rainfall areas than in lower-rainfall areas. This article belongs to the Collection Fire and Climate. [ABSTRACT FROM AUTHOR]

Background. The small portion of fires that escape initial attack (IA) have the greatest impacts on communities and incur most suppression costs. Early identification of fires with potential for escaping IA can prompt fire managers to order additional suppression resources, issue timely public warnings and plan longer-term containment strategies when they have the greatest potential for reducing a fire's impact. Aims. To develop IA models from a state-wide incident dataset containing novel variables that can be used to estimate the probability of IA when a new fire has been reported. Methods. A large dataset was compiled from bushfire incident records, geographical data and weather observations across the state of Victoria (n = 35 154) and was used to develop logistic regression models predicting the probability of initial attack success in grassland-, forest- and shrubland-dominated vegetation types. Key results. Models including input variables describing weather conditions, travel delay, slope and distance from roads were able to reasonably discriminate fires contained to 5 ha. Conclusions and implications. The models can be used to estimate IA success - using information available when the location of a new fire can be estimated - and they can be used to prompt planning for larger fires. [ABSTRACT FROM AUTHOR]

The paper presents a method of determining the robustness of solutions of systems of interval linear equations (ILEs). The method can be applied also for the ILE systems for which it has been impossible to find solutions so far or for which solutions in the form of improper intervals have been obtained (which cannot be implemented in practice). The research conducted by the authors has shown that for many problems it is impossible to arrive at ideal solutions that would be fully robust to data uncertainty. However, partially robust solutions can be obtained, and those with the highest robustness can be selected and put into practice. The paper shows that the degree of robustness to the uncertainty of the entire system can be calculated on the basis of the degrees of robustness of individual equations, which greatly simplifies calculations. The presented method is illustrated with a series of examples (also benchmark ones) that facilitate its understanding. It is an extension of the authors’ previously published method for first-order ILEs.

Changes in wildland fuels with time since fire affect the behaviour and impact of bushfires. The majority of research into fuel dynamics has generally been limited to changes in the load of fine dead surface fuels in forest ecosystems. Fuel dynamics in shrub dominated ecosystems are more complicated as most available fuel is comprised of living vegetation. The historical frequency of fire events influences the composition of plant functional response types and physical structure of post fire regrowth in these vegetation types. The composition and form of post fire vegetation also changes with time due to the lifecycles of the regenerating species. The structural form of the community will subsequently influence the behaviour of a further fire and the conditions under which it will burn. [ABSTRACT FROM AUTHOR]

Computing with words is a way to artificial, human-like thinking. The paper shows some new possibilities of solving difficult problems of computing with words which are offered by relative-distance-measure RDM models of fuzzy membership functions. Such models are based on RDM interval arithmetic. The way of calculation with words was shown using a specific problem of flight delay formulated by Lotfi Zadeh. The problem seems easy at first sight, but according to the authors’ knowledge it has not been solved yet. Results produced with the achieved solution were tested. The investigations also showed that computing with words sometimes offers possibilities of achieving better problem solutions than with the human mind.

The aim of the research described in this article is to work out a method to estimate the demand for freight transport in a situation when no historical data are available, thus rendering it impossible to apply methods based on time series data. The method presented in this article was developed and verified on the basis of an analysis of potential inland shipping operations on the Oder Waterway to/from the seaports in Szczecin and Świnoujście, assuming that the waterway has been upgraded to navigability class III. The analysis was predicated on a demand survey performed among cargo shippers. The obtained research results made it possible to specify the advantages and drawbacks of forecasting based on qualitative methods, and to identify the factors which significantly reduce the reliability of freight transport forecasts.

Abstract Background Microarrays are commonly used to investigate both the therapeutic potential and functional effects of RNA interfering (RNAi) oligonucleotides such as microRNA (miRNA) and small interfering RNA (siRNA). However, the resulting datasets are often challenging to interpret as they include extensive information relating to both indirect transcription effects and off-target interference events. Method In an attempt to refine the utility of microarray expression data when evaluating the direct transcriptional affects of an RNAi agent we have developed SBSE (Simple Bayesian Seed Estimate). The key assumption implemented in SBSE is that both direct regulation of transcription by miRNA, and siRNA off-target interference, can be estimated using the differential distribution of an RNAi sequence (seed) motif in a ranked 3' untranslated region (3' UTR) sequence repository. SBSE uses common microarray summary statistics (i.e. fold change) and a simple Bayesian analysis to estimate how the RNAi agent dictated the observed differential expression profile. On completion a trace of the estimate and the location of the optimal partitioning of the dataset are plotted within a simple graphical representation of the 3'UTR landscape. The combined estimates define the differential distribution of the query motif within the dataset and by inference are used to quantify the magnitude of the direct RNAi transcription effect. Results SBSE has been evaluated using five diverse human RNAi microarray focused investigations. In each instance SBSE unambiguously identified the most likely location of the direct RNAi effects for each of the differential gene expression profiles. Conclusion These analyses indicate that miRNA with conserved seed regions may share minimal biological activity and that SBSE can be used to differentiate siRNAs of similar efficacy but with different off-target signalling potential.

Background: Long-term persistence of Ebola virus (EBOV) in immunologically privileged sites has been implicated in recent outbreaks of Ebola virus disease (EVD) in Guinea and the Democratic Republic of Congo. This study was designed to understand how the acute course of EVD, convalescence, and host immune and genetic factors may play a role in prolonged viral persistence in semen., Methods: A cohort of 131 male EVD survivors in Liberia were enrolled in a case-case study. "Early clearers" were defined as those with 2 consecutive negative EBOV semen test results by real-time reverse-transcription polymerase chain reaction (rRT-PCR) ≥2 weeks apart within 1 year after discharge from the Ebola treatment unit or acute EVD. "Late clearers" had detectable EBOV RNA by rRT-PCR >1 year after discharge from the Ebola treatment unit or acute EVD. Retrospective histories of their EVD clinical course were collected by questionnaire, followed by complete physical examinations and blood work., Results: Compared with early clearers, late clearers were older (median, 42.5 years; P < .001) and experienced fewer severe clinical symptoms (median 2, P = .006). Late clearers had more lens opacifications (odds ratio, 3.9 [95% confidence interval, 1.1-13.3]; P = .03), after accounting for age, higher total serum immunoglobulin G3 (IgG3) titers (P = .005), and increased expression of the HLA-C*03:04 allele (0.14 [.02-.70]; P = .007)., Conclusions: Older age, decreased illness severity, elevated total serum IgG3 and HLA-C*03:04 allele expression may be risk factors for the persistence of EBOV in the semen of EVD survivors. EBOV persistence in semen may also be associated with its persistence in other immunologically protected sites, such as the eye., Competing Interests: Potential conflicts of interest. A. Kofman reports support for attending meetings and/or travel from the CDC Foundation. R. S. B. reports $11 000 in grants or contracts from the University of Mississippi Medical Centre and $7500 in contracts or grants from the Federation University Centre for Health Transformation and Innovation, both unrelated to this work; a registration fee waiver ($650) in support of attending the Australian Society for Microbiology 2022 meeting; World Intellectual Property Organization patent WO2019060840, (Removing Interfering Host Nucleic Acids for Molecular Parasite Detection; granted 28 March 2019; patent royalties to the CDC Division of Parasitic Diseases and Malaria); unpaid participation on the Surveillance Cross-cutting Subgroup of the World Health Organization Neglected Tropical Disease Diagnostic Technical Advisory Group, unpaid participation as a member of the Strongyloides subgroup of the WHO Technical Advisory Group on Schistosomiasis and Transmitted Helminthiases, and unpaid participation at a WHO policy meeting with Dora Buonfrate of Ospidale Sacra Cuore (Italy) and Antonio Montresor of the WHO (Diagnostic Methods for the Control of Strongyloidiasis; 29 September 2020); and leadership or fiduciary roles with Strongyloides Australia (as vice president), the Australian Society for Parasitology Education Committee, and the Australian Society for Infectious Diseases Zoonosis Special Interest Group. S. H. H. reports consulting fees paid to the author from Leavitt Associates; support for attending meetings and/or travel from their employer (University of Nebraska Medical Center); patents planned, issued or pending (none related to this work); participation on the advisory board of the HHS National Coordinator of IT; and ownership of stock or stock options (none related to this article). All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2022.)

Background: Malaria rapid diagnostic tests (RDTs) based on the detection of the Plasmodium falciparum histidine-rich protein 2 (HRP2) antigen are widely used for detection of active infection with this parasite and are the only practical malaria diagnostic test in some endemic settings. External validation of RDT results from field surveys can confirm appropriate RDT performance., Methods: A community-based cross-sectional survey was conducted between July and November 2017 enrolling participants of all ages in households from 15 villages in four border regions of Tanzania: Geita, Kigoma, Mtwara and Ruvuma. All participants had an RDT performed in the field and provided a blood sample for later laboratory multiplex antigen detection of HRP2. In assessing the continuous HRP2 levels in participant blood versus RDT result, dose-response logistic regression provided quantitative estimates for HRP2 limit of detection (LOD)., Results: From the 15 study villages, 6941 persons were enrolled that had a RDT at time of enrollment and provided a DBS for later laboratory antigen detection. RDT positive prevalence for the HRP2 band by village ranged from 20.0 to 43.6%, but the magnitude of this prevalence did not have an effect on the estimated LOD of RDTs utilized in different villages. Overall, HRP2 single-target tests had a lower LOD at the 95% probability of positive RDT (4.3 ng/mL; 95% CI 3.4-5.4) when compared to pLDH/HRP2 dual target tests (5.4 ng/mL; 4.5-6.3), though this difference was not significant. With the exception of one village, all other 14 villages (93.3%) showed RDT LOD estimates at 90% probability of positive RDT between 0.5 and 12.0 ng/mL., Conclusions: Both HRP2-only and pLDH/HRP2 combo RDTs utilized in a 2017 Tanzania cross-sectional survey of border regions generally performed well, and reliably detected HRP2 antigen in the low ng/mL range. Though single target tests had lower levels of HRP2 detection, both tests were within similar ranges among the 15 villages. Comparison of quantitative HRP2 detection limits among study sites can help interpret RDT testing results when generating population prevalence estimates for malaria infection., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

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., (© 2022. The Author(s).)

Background: Plasmodium blood-stage infections can be identified by assaying for protein products expressed by the parasites. While the binary result of an antigen test is sufficient for a clinical result, greater nuance can be gathered for malaria infection status based on quantitative and sensitive detection of Plasmodium antigens and machine learning analytical approaches., Methods: Three independent malaria studies performed in Angola and Haiti enrolled persons at health facilities and collected a blood sample. Presence and parasite density of P. falciparum infection was determined by microscopy for a study in Angola in 2015 (n = 193), by qRT-PCR for a 2016 study in Angola (n = 208), and by qPCR for a 2012-2013 Haiti study (n = 425). All samples also had bead-based detection and quantification of three Plasmodium antigens: pAldolase, pLDH, and HRP2. Decision trees and principal component analysis (PCA) were conducted in attempt to categorize P. falciparum parasitemia density status based on continuous antigen concentrations., Results: Conditional inference trees were trained using the known P. falciparum infection status and corresponding antigen concentrations, and PCR infection status was predicted with accuracies ranging from 73-96%, while level of parasite density was predicted with accuracies ranging from 59-72%. Multiple decision nodes were created for both pAldolase and HRP2 antigens. For all datasets, dichotomous infectious status was more accurately predicted when compared to categorization of different levels of parasite densities. PCA was able to account for a high level of variance (>80%), and distinct clustering was found in both dichotomous and categorical infection status., Conclusions: This pilot study offers a proof-of-principle of the utility of machine learning approaches to assess P. falciparum infection status based on continuous concentrations of multiple Plasmodium antigens., Competing Interests: The authors have declared that no competing interests exist.

Rift Valley fever virus (RVFV) is endemic in sub-Saharan Africa (SSA), with outbreaks reported in the Arabian Peninsula and throughout SSA. The natural reservoir for RVFV are ruminants, with livestock populations exceeding 50% exposure rates in some areas of SSA. Transmission to humans can occur through exposure to infected livestock products or multiple species of mosquito vectors. In 2013 and 2014, cross-sectional surveys occurred in two districts of Nacala-a-Velha and Mecubúri in northern Mozambique, and participants provided blood samples for later serological assays. IgG against the N protein of RVFV was detected through multiplex bead assay (MBA). Of the 2,278 persons enrolled between the two surveys and study sites, 181 (7.9%, 95% confidence interval (CI): 6.9%-9.1%) were found to be IgG seropositive with increasing seroprevalence with older age and significantly higher seroprevalence in Nacala-a-Velha (10.5%, 8.8%-12.5%) versus Mecubúri (5.7%, 4.5%-7.1%). Seroprevalence estimates were not significantly different between the 2013 and 2014 surveys. Significant spatial clustering of IgG positive persons were consistent among surveys and within the two districts, pointing toward the consistency of serology data for making population-level assumptions regarding RVFV seroprevalence. A subset of persons ( n  = 539) provided samples for both the 2013 and 2014 surveys, and a low percentage (0.81%) of these were found to seroconvert between these two surveys. Including the RVFV N protein in an MBA antigen panel could assist elucidate RVFV exposure in SSA. IMPORTANCE Due to sporadic transmission, human contact with Rift Valley Fever Virus (RVFV) is difficult to ascertain at a population level. Detection of antibodies against RVFV antigens assist in estimating exposure as antibodies remain in the host long after the virus has been cleared. In this study, we show that antibodies against RVFV N protein can be detected from dried blood spot (DBS) samples being assayed by multiplex bead assay. DBS from two districts in northern Mozambique were tested for IgG against the N protein, and 7.9% of all enrolled persons were seropositive. Older persons, males, and persons residing closer to the coast had higher RVFV N protein seroprevalence. Spatial clustering of IgG positive persons was noted in both districts. These results show low exposure rates to RVFV in these two northern districts in Mozambique, and the ability to perform serology for the RVFV N protein from dried blood samples.

Immunoglobulin (Ig) production during and after infection with Plasmodium parasites is one of the greatest adaptive immune defenses the human host has against this parasite. Infection with P. falciparum has been shown to induce different B cell maturation responses dependent upon the age of the patient, number of previous exposures, and severity of the disease. Described here are dynamics of Ig responses to a panel of 32 P. falciparum antigens by patients followed for 42 days and classified individuals as showing characteristics of an apparent first P. falciparum infection (naïve) or a repeat exposure (non-naïve). Six parameters were modeled to characterize the dynamics of IgM, IgG 1 , IgG 3 , and IgA for these two exposure groups with differences assessed among Ig isotypes/subclasses and unique antigens. Naïve patients had significantly longer periods of time to reach peak Ig titer (range 4-7 days longer) and lower maximum Ig titers when compared with non-naïve patients. Modeled time to seronegativity was significantly higher in non-naïve patients for IgM and IgA, but not for the two IgG subclasses. IgG 1 responses to Rh2030, HSP40, and PfAMA1 were at the highest levels for non-naïve participants and may be used to predict previous or nascent exposure by themselves. The analyses presented here demonstrate the differences in the development of the Ig response to P. falciparum if the infection represents a boosting response or a primary exposure. Consistency in Ig isotype/subclasses estimates and specific data for P. falciparum antigens can better guide interpretation of seroepidemiological data among symptomatic persons., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rogier, Nace, Dimbu, Wakeman, Beeson, Drakeley, Tetteh and Plucinski.)

Through active surveillance and contact tracing from outpatients, we aimed to identify and characterize SARS-CoV-2 variants circulating in Porto Velho-Rondônia, a city in the Brazilian Amazon. As part of a prospective cohort, we gathered information from 2,506 individuals among COVID-19 patients and household contacts. Epidemiological data, nasopharyngeal swabs, and blood samples were collected from all participants. Nasopharyngeal swabs were tested for antigen rapid diagnostic test and reverse transcription-polymerase chain reaction (RT-PCR) followed by genomic sequencing. Blood samples underwent ELISA testing for IgA, IgG, and IgM antibody levels. From 757 specimens sequenced, three were identified as Mu variant, none of the individuals carrying this variant had a travel history in the previous 15 days before diagnosis. One case was asymptomatic and two presented mild symptoms. Two infected individuals from different households caring viruses with additional amino acid substitutions ORF7a P45L and ORF1a T1055A compared to the Mu virus reference sequence. One patient presented IgG levels. Our results highlight that genomic surveillance for SARS-CoV-2 variants can assist in detecting the emergency of SARS-CoV-2 variants in the community, before its identification in other parts of the country., (© 2022 The Authors. Journal of Medical Virology published by Wiley Periodicals LLC.)

Background: In low-transmission settings, accurate estimates of malaria transmission are needed to inform elimination targets. Detection of antimalarial antibodies provides exposure history, but previous studies have mainly relied on species-specific antigens. The use of chimeric antigens that include epitopes from multiple species of malaria parasites in population-based serological surveys could provide data for exposure to multiple Plasmodium species circulating in an area. Here, the utility of P. vivax/P. falciparum chimeric antigen for assessing serological responses was evaluated in Ethiopia, an endemic country for all four human malarias, and Costa Rica, where P. falciparum has been eliminated with reports of sporadic P. vivax cases., Methods: A multiplex bead-based assay was used to determine the seroprevalence of IgG antibodies against a chimeric malaria antigen (PvRMC-MSP1) from blood samples collected from household surveys in Ethiopia in 2015 (n = 7,077) and Costa Rica in 2015 (n = 851). Targets specific for P. falciparum (PfMSP1) and P. vivax (PvMSP1) were also included in the serological panel. Seroprevalence in the population and seroconversion rates were compared among the three IgG targets., Results: Seroprevalence in Costa Rica was 3.6% for PfMSP1, 41.5% for PvMSP1 and 46.7% for PvRMC-MSP1. In Ethiopia, seroprevalence was 27.6% for PfMSP1, 21.4% for PvMSP1, and 32.6% for PvRMC-MSP1. IgG levels in seropositive individuals were consistently higher for PvRMC-MSP1 when compared to PvMSP1 in both studies. Seroconversion rates were 0.023 for PvMSP1 and 0.03 for PvRMC-MSP1 in Costa Rica. In Ethiopia, seroconversion rates were 0.050 for PfMSP1, 0.044 for PvMSP1 and 0.106 for PvRMC-MSP1., Conclusions: Our data indicate that chimeric antigen PvRMC-MSP1 is able to capture antibodies to multiple epitopes from both prior P. falciparum and P. vivax infections, and suitable chimeric antigens can be considered for use in serosurveys with appropriate validation., Competing Interests: The authors have declared that no competing interests exist.

The majority of symptomatic malaria in sub-Saharan Africa is caused by Plasmodium falciparum . Infection with Plasmodium ovale is often not recorded and not considered clinically relevant. Here, we describe 8 cases of P ovale infection from 3 African countries-all of which were misdiagnosed at the presenting health facility., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Background: Rapid diagnostic tests (RDTs) are widely used for malaria diagnosis of both symptomatic and asymptomatic infections. Although RDTs are a reliable and practical diagnostic tool, the sensitivity of histidine-rich protein 2 (HRP2)-based RDTs can be reduced if pfhrp2 or pfhrp3 (pfhrp2/3) gene deletions exist in the Plasmodium falciparum parasite population. This study evaluated dried blood spot (DBS) samples collected from a national household survey to investigate the presence of pfhrp2/3 deletions and the performance of the RDT used in the cross-sectional survey in a low transmission setting., Methods: The 2015 Ethiopia Malaria Indicator Survey tested household members by RDT and collected DBS samples. DBS (n = 2648) from three regions in northern Ethiopia were tested by multiplex bead-based antigen detection assay after completion of the survey. The multiplex assay detected pan-Plasmodium lactate dehydrogenase (LDH), pAldolase, and HRP2 antigens in samples. Samples suspected for pfhrp2/3 gene deletions (pLDH and/or pAldolase positive but low or absent HRP2) were further investigated by molecular assays for gene deletions. Antigen results were also compared to each individual's RDT results. Dose-response logistic regression models were fit to estimate RDT level of detection (LOD) antigen concentrations at which 50, 75, 90, and 95% of the RDTs returned a positive result during this survey., Results: Out of 2,648 samples assayed, 29 were positive for pLDH or pAldolase antigens but low or absent for HRP2 signal, and 15 of these samples (51.7%) were successfully genotyped for pfhrp2/3. Of these 15 P. falciparum infections, eight showed single deletions in pfhrp3, one showed a single pfhrp2 deletion, and six were pfhrp2/3 double-deletions. Six pfhrp2 deletions were observed in Tigray and one in Amhara. Twenty-five were positive for HRP2 by the survey RDT while the more sensitive bead assay detected 30 HRP2-positive samples. A lower concentration of HRP2 antigen generated a positive test result by RDT compared to pLDH (95% LOD: 16.9 ng/mL vs. 319.2 ng/mL, respectively)., Conclusions: There is evidence of dual pfhrp2/3 gene deletions in the Tigray and Amhara regions of Ethiopia in 2015. As the prevalence of malaria was very low (< 2%), it is difficult to make strong conclusions on RDT performance, but these results challenge the utility of biomarkers in household surveys in very low transmission settings., (© 2022. The Author(s).)

High case counts after the Gamma (P. 1) variant of severe acute respiratory syndrome coronavirus 2 emerged in Brazil raised concerns that previously infected persons might become reinfected. Investigation of a cluster of coronavirus disease cases in Parintins, in the Brazilian Amazon, suggested household transmission but did not identify high rates of reinfection.

The identification and characterization of proteins produced during human infection with Plasmodium spp. have guided the malaria community in research, diagnosis, epidemiology, and other efforts. Recently developed methods for the detection of these proteins (antigens) in the laboratory have provided new types of data that can inform the evaluation of malaria diagnostics, epidemiological investigations, and overall malaria control strategies. Here, the focus is primarily on antigens that are currently known to be detectable in human specimens and on their impact on the understanding of malaria in human populations. We highlight historical and contemporary laboratory assays for malaria antigen detection, the concept of an antigen profile for a biospecimen, and ways in which binary results for a panel of antigens could be interpreted and utilized for different analyses. Particular emphasis is given to the direct comparison of field-level malaria diagnostics and laboratory antigen detection for the development of an external evaluation scheme. The current limitations of laboratory antigen detection are considered, and the future of this developing field is discussed.

Human Plasmodium infection produces a robust adaptive immune response. Time courses for 104 children followed for 42 days after initiation of Plasmodium falciparum chemotherapy were assayed for antibody levels to the five isotypes of human immunoglobulins (Ig) and 4 subclasses of IgG for 32 P. falciparum antigens encompassing all 4 parasite stages of human infection. IgD and IgE against these antigens were undetectable at 1:100 serum concentration, but other Ig isotypes and IgG subclasses were consistently observed against all antigens. Five quantitative parameters were developed to directly compare Ig response among isotypes and antigens: C max , maximum antibody level; Δ C , difference between C max and the antibody level at Day 0; t max , time in days to reach C max ; t 1/2 , Ig signal half-life in days; t neg , estimated number of days until complete loss of Ig signal. Classical Ig patterns for a bloodborne pathogen were seen with IgM showing early t max and IgG production highest among Ig isotypes. However, some unexpected trends were observed such as IgA showing a biphasic pattern for many antigens. Variability among these dynamics of Ig acquisition and loss was noted for different P. falciparum antigens and able to be compared both quantitatively and statistically. This parametrization methodology allows direct comparison of Ig isotypes produced against various Plasmodium antigens following malaria infection, and the same methodology could be applied to other longitudinal serologic studies from P. falciparum or different pathogens. Specifically for P. falciparum seroepidemiological studies, reliable and quantitative estimates regarding the IgG dynamics in human populations can better optimize modeling efforts for serological outputs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Rogier, Nace, Dimbu, Wakeman, Pohl, Beeson, Drakeley, Tetteh and Plucinski.)

Malaria incidence is generally lower in cities than rural areas. However, reported urban malaria incidence may not accurately reflect the level of ongoing transmission, which has potentially large implications for prevention efforts. To guide mosquito net distribution, we assessed the extent of malaria transmission in Conakry, Guinea, in 2018. We found evidence of active malaria transmission.

Outbreaks of cyclosporiasis, a food-borne illness caused by the coccidian parasite Cyclospora cayetanensis have increased in the USA in recent years, with approximately 2300 laboratory-confirmed cases reported in 2018. Genotyping tools are needed to inform epidemiological investigations, yet genotyping Cyclospora has proven challenging due to its sexual reproductive cycle which produces complex infections characterized by high genetic heterogeneity. We used targeted amplicon deep sequencing and a recently described ensemble-based distance statistic that accommodates heterogeneous (mixed) genotypes and specimens with partial genotyping data, to genotype and cluster 648 C. cayetanensis samples submitted to CDC in 2018. The performance of the ensemble was assessed by comparing ensemble-identified genetic clusters to analogous clusters identified independently based on common food exposures. Using these epidemiologic clusters as a gold standard, the ensemble facilitated genetic clustering with 93.8% sensitivity and 99.7% specificity. Hence, we anticipate that this procedure will greatly complement epidemiologic investigations of cyclosporiasis.

Background: Between 2011 and 2018, an estimated 134.8 million pyrethroid-treated long-lasting insecticidal nets (LLINs) were distributed nationwide in the Democratic Republic of Congo (DRC) for malaria control. Pyrethroid resistance has developed in DRC in recent years, but the intensity of resistance and impact on LLIN efficacy was not known. Therefore, the intensity of resistance of Anopheles gambiae sensu lato (s.l.) to permethrin and deltamethrin was monitored before and after a mass distribution of LLINs in Kinshasa in December 2016, and in 6 other sites across the country in 2017 and 11 sites in 2018., Methods: In Kinshasa, CDC bottle bioassays using 1, 2, 5, and 10 times the diagnostic dose of permethrin and deltamethrin were conducted using An. gambiae s.l. collected as larvae and reared to adults. Bioassays were conducted in four sites in Kinshasa province 6 months before a mass distribution of deltamethrin-treated LLINs and then two, six, and 10 months after the distribution. One site in neighbouring Kongo Central province was used as a control (no mass campaign of LLIN distribution during the study). Nationwide intensity assays were conducted in six sites in 2017 using CDC bottle bioassays and in 11 sites in 2018 using WHO intensity assays. A sub-sample of An. gambiae s.l. was tested by PCR to determine species composition and frequency of kdr-1014F and 1014S alleles., Results: In June 2016, before LLIN distribution, permethrin resistance intensity was high in Kinshasa; the mean mortality rate was 43% at the 5× concentration and 73% at the 10× concentration. Bioassays at 3 time points after LLIN distribution showed considerable variation by site and time and there was no consistent evidence for an increase in pyrethroid resistance intensity compared to the neighbouring control site. Tests of An. gambiae s.l. in 6 sites across the country in 2017 and 11 sites in 2018 showed all populations were resistant to the diagnostic doses of 3 pyrethroids. In 2018, the intensity of resistance varied by site, but was generally moderate for all three pyrethroids, with survivors at ×5 the diagnostic dose. Anopheles gambiae sensu stricto (s.s.) was the most common species identified across 11 sites in DRC, but in Kinshasa, An. gambiae s.s. (91%) and Anopheles coluzzii (8%) were sympatric., Conclusions: Moderate or high intensity pyrethroid resistance was detected nationwide in DRC and is a serious threat to sustained malaria control with pyrethroid LLINs. Next generation nets (PBO nets or bi-treated nets) should be considered for mass distribution.

Antimalarial drugs have long half-lives, so clinical trials to monitor their efficacy require long periods of follow-up to capture drug failure that may become patent only weeks after treatment. Reinfections often occur during follow-up, so robust methods of distinguishing drug failures (recrudescence) from emerging new infections are needed to produce accurate failure rate estimates. Molecular correction aims to achieve this by comparing the genotype of a patient's pretreatment (initial) blood sample with that of any infection that occurs during follow-up, with matching genotypes indicating drug failure. We use an in silico approach to show that the widely used match-counting method of molecular correction with microsatellite markers is likely to be highly unreliable and may lead to gross under- or overestimates of the true failure rates, depending on the choice of matching criterion. A Bayesian algorithm for molecular correction was previously developed and utilized for analysis of in vivo efficacy trials. We validated this algorithm using in silico data and showed it had high specificity and generated accurate failure rate estimates. This conclusion was robust for multiple drugs, different levels of drug failure rates, different levels of transmission intensity in the study sites, and microsatellite genetic diversity. The Bayesian algorithm was inherently unable to accurately identify low-density recrudescence that occurred in a small number of patients, but this did not appear to compromise its utility as a highly effective molecular correction method for analyzing microsatellite genotypes. Strong consideration should be given to using Bayesian methodology to obtain accurate failure rate estimates during routine monitoring trials of antimalarial efficacy that use microsatellite markers.

Sexually reproducing pathogens such as Cyclospora cayetanensis often produce genetically heterogeneous infections where the number of unique sequence types detected at any given locus varies depending on which locus is sequenced. The genotypes assigned to these infections quickly become complex when additional loci are analysed. This genetic heterogeneity confounds the utility of traditional sequence-typing and phylogenetic approaches for aiding epidemiological trace-back, and requires new methods to address this complexity. Here, we describe an ensemble of two similarity-based classification algorithms, including a Bayesian and heuristic component that infer the relatedness of C. cayetanensis infections. The ensemble requires a set of haplotypes as input and assigns arbitrary distances to specimen pairs reflecting their most likely relationships. The approach was applied to data generated from a test cohort of 88 human fecal specimens containing C. cayetanensis, including 30 from patients whose infections were associated with epidemiologically defined outbreak clusters of cyclosporiasis. The ensemble assigned specimens to plausible clusters of genetically related infections despite their complex haplotype composition. These relationships were corroborated by a significant number of epidemiological linkages (P < 0.0001) suggesting the ensemble's utility for aiding epidemiological trace-back investigations of cyclosporiasis.

Background: The World Health Organization recommends the use of artemisinin-based combination therapy (ACT) to treat uncomplicated malaria for the control of malaria across the world. There are several types of ACT used across malaria-endemic countries, yet there is little information about preferences and adherence practices regarding different types of ACT. The objective of this study was to evaluate levels of adherence to two types of ACT, artemether-lumefantrine (AL) and artesunate + amodiaquine (ASAQ), for the treatment of uncomplicated malaria among prescribers and patients in Guinea in 2016., Methods: The study included a review of records of malaria patients and three health-facility, cross-sectional surveys. Patients diagnosed with uncomplicated malaria and prescribed ACT (n = 1830) were recruited and visited in their home after receiving the medication and administered a questionnaire regarding ACT adherence. Prescribers (n = 115) and drug dispensers (n = 43) were recruited at the same public health facilities and administered questionnaires regarding prescribing practices and opinions regarding the national treatment policies and protocols., Results: According to the registry review, 35.8% of all-cause consultations were recorded as malaria. Of these, 26.6% were diagnosed clinically without documentation of laboratory confirmation. The diagnosis of uncomplicated malaria represented 64.1% of malaria cases among children under 5 years and 74.9% of those 5 years of age and older. An ACT was prescribed for 83.5% of cases of uncomplicated malaria. Among participants in the study, ACT adherence was 95.4% (95% CI 94.4, 96.3). Overall, about one in four patients (23.4%; 95% CI 21.5, 25.3) reported experiencing adverse events. While patients prescribed ASAQ were significantly more likely to report experiencing adverse effects than patients on AL (p < 0.001), given the overall high adherence, there was no evidence of a statistically significant difference in adherence between AL and ASAQ. Patients 5 years or older who reported experiencing adverse events were more likely to be non-adherent., Conclusion: Although there were more reported adverse events associated with ASAQ when compared with AL, both prescribers and patients were found to be mostly adherent to ACT for the treatment of malaria, regardless of ACT type.