Search

Background: Malaria transmission in Tanzania has declined significantly over the last 2 decades due to scaled-up control interventions. However, recent confirmation of artemisinin partial resistance (ART-R) in Kagera region in northwest Tanzania threatens the ongoing efforts to eliminate malaria in the country. This study was conducted according to the World Health Organization recommendation to generate evidence of malaria burden in areas with confirmed ART-R as the first step before developing a response strategy to the resistance., Methods: We assessed the local burden of malaria in Kagera region by geospatial analysis, using data collected retrospectively from health facilities and community surveys from 2015 to 2023 to identify malaria hot spots., Results: From 2017 to 2023, a total of 8 124 363 suspected malaria cases were reported by health facilities, and 2 983 717 (36.7% [95% range across wards, 22.7%-50.7%]) tested positive by rapid diagnostic tests. Test positivity rates were similar among patients aged <5 years (33.1% [95% range, 19.7%-46.5%]) and those aged ≥5 years (33.7% [21.0%-46.5%]). The malaria prevalence was 10.0% (95% range across wards, 5.1%-14.9% [n = 84 999 of 853 761]) in pregnant women and 26.1% (11.7%-40.6% [n = 3409 of 13 065]) in schoolchildren. Despite high temporal variations, we identified hot spots and cold spots, including persistently high burden in 69 of 192 wards (35.9%)., Conclusions: The malaria burden in Kagera exhibited high temporal and spatial heterogeneity, with schoolchildren showing the highest prevalence. This demographic pattern underlines the need for targeted interventions and provides evidence for developing an ART-R response for the region., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Dengue is endemic in Vietnam with circulation of all four serotypes (DENV1-4) all year-round. It is hard to estimate the disease's true serotype-specific transmission patterns from cases due to its high asymptomatic rate, low reporting rate and complex immunity and transmission dynamics. Seroprevalence studies have been used to great effect for understanding patterns of dengue transmission. We tested 991 population serum samples (ages 1-30 years, collected 2013 to 2017), 531 from Ho Chi Minh City and 460 from Khanh Hoa in Vietnam, using a flavivirus protein microarray assay. By applying our previously developed inference framework to the antibody profiles from this assay, we can (1) determine proportions of a population that have not been infected or infected, once, or more than once, and (2) infer the infecting serotype in those infected once. With these data, we then use mathematical models to estimate the force of infection (FOI) for all four DENV serotypes in HCMC and KH over 35 years up to 2017. Models with time-varying or serotype-specific DENV FOI assumptions fit the data better than constant FOI. Annual dengue FOI ranged from 0.005 (95%CI: 0.003-0.008) to 0.201 (95%CI: 0.174-0.228). FOI varied across serotypes, higher for DENV1 (95%CI: 0.033-0.048) and DENV2 (95%CI: 0.018-0.039) than DENV3 (95%CI: 0.007-0.010) and DENV4 (95%CI: 0.010-0.016). The use of the PMA on serial age-stratified cross-sectional samples increases the amount of information on transmission and population immunity, and should be considered for future dengue serological surveys, particularly to understand population immunity given vaccines with differential efficacy against serotypes, however, there remains limits to what can be inferred even using this assay., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Phuong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Influenza virus seasonality, synchronicity, and vaccine supply differ substantially between temperate and tropical settings, and optimal vaccination strategy may differ on this basis. Many national vaccine recommendations focus on high-risk groups, elderly populations, and healthcare workers despite previous analyses demonstrating broad benefits to vaccinating younger high-contact age groups. In this study, we parameterized an age-structured nonseasonal asynchronous epidemiological model of influenza virus transmission for a tropical low-income setting. We evaluated timing and age allocation of vaccines across vaccine supplies ranging from 10 to 90% using decade-based age groups. Year-round vaccination was beneficial when compared with more concentrated annual vaccine distribution. When targeting a single age group for vaccine prioritization, maximum vaccine allocation to the 10-19 high-contact age group minimized annual influenza mortality for all but one vaccine supply. When evaluating across all possible age allocations, optimal strategies always allocated a plurality of vaccines to school-age children (10-19). The converse, however, was not true as not all strategies allocating a plurality to children aged 10-19 minimized mortality. Allocating a high proportion of vaccine supply to the 10-19 age group is necessary but not sufficient to minimize annual mortality as distribution of remaining vaccine doses to other age groups also needs to be optimized. Strategies focusing on indirect benefits (vaccinating children) showed higher variance in mortality outcomes than strategies focusing on direct benefits (vaccinating the elderly). However, the indirect benefit approaches showed a lower mean mortality and a lower minimum mortality than vaccination focused on the elderly., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population and how this heterogeneity affects virus evolution. Here, we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of two H3N2 strains, A/Hong Kong/45/2019 and A/Perth/16/2009, affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that were fixed in influenza variants after 2020 cause greater escape from sera from younger individuals compared with adults. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups and suggest approaches to understand how this heterogeneous selection shapes viral evolution., Competing Interests: Declaration of interests J.D.B. is on the scientific advisory boards of Apriori Bio, Invivyd, Aerium Therapeutics, and the Vaccine Company. J.D.B., A.N.L., and F.C.W. receive royalty payments as inventors on Fred Hutch licensed patents related to viral deep mutational scanning. H.Y.C. reports consulting with Ellume, Pfizer, and the Bill and Melinda Gates Foundation. She has served on advisory boards for Vir, Merck, and Abbvie. She has conducted CME teaching with Medscape, Vindico, and Clinical Care Options. She has received research funding from Gates Ventures and support and reagents from Ellume and Cepheid outside of the submitted work. J.A.E. receives institutional funding from AstraZeneca, Merck, GlaxoSmithKline, and Pfizer. She is a consultant for Abbvie, AstraZeneca, GlaxoSmithKline, Meissa Vaccines, Moderna, Pfizer, and SanofiPasteur. A.L.G. reports contract testing from Abbott, Cepheid, Novavax, Pfizer, Janssen, and Hologic and research support from Gilead outside of the submitted work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Historically Plasmodium falciparum has followed a pattern of drug resistance first appearing in low-transmission settings before spreading to high-transmission settings. Several features of low-transmission regions are hypothesized as explanations: higher chance of symptoms and treatment seeking, better treatment access, less within-host competition among clones and lower rates of recombination. Here, we test whether importation of drug-resistant parasites is more likely to lead to successful emergence and establishment in low-transmission or high-transmission periods of the same epidemiological setting, using a spatial, individual-based stochastic model of malaria and drug-resistance evolution calibrated for Burkina Faso. Upon controlling for the timing of importation of drug-resistant genotypes and examination of key model variables, we found that drug-resistant genotypes imported during the low-transmission season were (i) more susceptible to stochastic extinction due to the action of genetic drift, and (ii) more likely to lead to establishment of drug resistance when parasites are able to survive early stochastic loss due to drift. This implies that rare importation events are more likely to lead to establishment if they occur during a high-transmission season, but that constant importation (e.g. neighbouring countries with high levels of resistance) may produce a greater risk during low-transmission periods.

Delaying and slowing antimalarial drug resistance evolution is a priority for malaria-endemic countries. Until novel therapies become available, the mainstay of antimalarial treatment will continue to be artemisinin-based combination therapy (ACT). Deployment of different ACTs can be optimized to minimize evolutionary pressure for drug resistance by deploying them as a set of co-equal multiple first-line therapies (MFT) rather than rotating therapies in and out of use. Here, we consider one potential detriment of MFT policies, namely, that the simultaneous deployment of multiple ACTs could drive the evolution of different resistance alleles concurrently and that these resistance alleles could then be brought together by recombination into double-resistant or triple-resistant parasites. Using an individual-based model, we compare MFT and cycling policies in malaria transmission settings ranging from 0.1% to 50% prevalence. We define a total risk measure for multi-drug resistance (MDR) by summing the area under the genotype-frequency curves (AUC) of double- and triple-resistant genotypes. When prevalence ≥ 1%, total MDR risk ranges from statistically similar to 80% lower under MFT policies than under cycling policies, irrespective of whether resistance is imported or emerges de novo. At 0.1% prevalence, there is little statistical difference in MDR risk between MFT and cycling., (© 2024. The Author(s).)

Artemisinin combination therapies (ACTs) are highly effective at treating uncomplicated Plasmodium falciparum malaria, but the emergence of the new pfkelch13 R561H mutation in Rwanda, associated with delayed parasite clearance, suggests that interventions are needed to slow its spread. Using a Rwanda-specific spatial calibration of an individual-based malaria model, we evaluate 26 strategies aimed at minimizing treatment failures and delaying the spread of R561H after 3, 5 and 10 years. Lengthening ACT courses and deploying multiple first-line therapies (MFTs) reduced treatment failures after 5 years when compared to the current approach of a 3-d course of artemether-lumefantrine. The best among these options (an MFT policy) resulted in median treatment failure counts that were 49% lower and a median R561H allele frequency that was 0.15 lower than under baseline. New approaches to resistance management, such as triple ACTs or sequential courses of two different ACTs, were projected to have a larger impact than longer ACT courses or MFT; these were associated with median treatment failure counts in 5 years that were 81-92% lower than the current approach. A policy response to currently circulating artemisinin-resistant genotypes in Africa is urgently needed to prevent a population-wide rise in treatment failures., (© 2023. The Author(s).)

Introduction: It is well known that influenza and other respiratory viruses are wintertime-seasonal in temperate regions. However, respiratory disease seasonality in the tropics is less well understood. In this study, we aimed to characterise the seasonality of influenza-like illness (ILI) and influenza virus in Ho Chi Minh City, Vietnam., Methods: We monitored the daily number of ILI patients in 89 outpatient clinics from January 2010 to December 2019. We collected nasal swabs and tested for influenza from a subset of clinics from May 2012 to December 2019. We used spectral analysis to describe the periodic signals in the system. We evaluated the contribution of these periodic signals to predicting ILI and influenza patterns through lognormal and gamma hurdle models., Results: During 10 years of community surveillance, 66 799 ILI reports were collected covering 2.9 million patient visits; 2604 nasal swabs were collected, 559 of which were PCR-positive for influenza virus. Both annual and nonannual cycles were detected in the ILI time series, with the annual cycle showing 8.9% lower ILI activity (95% CI 8.8% to 9.0%) from February 24 to May 15. Nonannual cycles had substantial explanatory power for ILI trends (ΔAIC=183) compared with all annual covariates (ΔAIC=263) in lognormal regression. Near-annual signals were observed for PCR-confirmed influenza but were not consistent over time or across influenza (sub)types. The explanatory power of climate factors for ILI and influenza virus trends was weak., Conclusion: Our study reveals a unique pattern of respiratory disease dynamics in a tropical setting influenced by both annual and nonannual drivers, with influenza dynamics showing near-annual periodicities. Timing of vaccination campaigns and hospital capacity planning may require a complex forecasting approach., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: As we continue the fourth year of the COVID-19 epidemic, SARS-CoV-2 infections still cause high morbidity and mortality in the United States. During 2020-2022, COVID-19 was one of the leading causes of death in the United States and by far the leading cause among infectious diseases. Vaccination uptake remains low despite this being an effective burden reducing intervention. The development of COVID-19 therapeutics provides hope for mitigating severe clinical outcomes. This modeling study examines combined strategies of vaccination and treatment to reduce the burden of COVID-19 epidemics over the next decade., Methods: We use a validated mathematical model to evaluate the reduction of incident cases, hospitalized cases, and deaths in the United States through 2033 under various levels of vaccination and treatment coverage. We assume that future seasonal transmission patterns for COVID-19 will be similar to those of influenza virus and account for the waning of infection-induced immunity and vaccine-induced immunity in a future with stable COVID-19 dynamics. Due to uncertainty in the duration of immunity following vaccination or infection, we consider three exponentially distributed waning rates, with means of 365 days (1 year), 548 days (1.5 years), and 730 days (2 years). We also consider treatment failure, including rebound frequency, as a possible treatment outcome., Results: As expected, universal vaccination is projected to eliminate transmission and mortality. Under current treatment coverage (13.7%) and vaccination coverage (49%), averages of 81,000-164,600 annual reported deaths, depending on duration of immunity, are expected by the end of this decade. Annual mortality in the United States can be reduced below 50,000 per year with 52-80% annual vaccination coverage and below 10,000 annual deaths with 59-83% annual vaccination coverage, depending on duration of immunity. Universal treatment reduces hospitalizations by 88.6% and deaths by 93.1% under current vaccination coverage. A reduction in vaccination coverage requires a comparatively larger increase in treatment coverage in order for hospitalization and mortality levels to remain unchanged., Conclusions: Adopting universal vaccination and universal treatment goals in the United States will likely lead to a COVID-19 mortality burden below 50,000 deaths per year, a burden comparable to that of influenza virus., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Swine pathogens have a long history of zoonotic transmission to humans, occasionally leading to sustained outbreaks or pandemics. Through a retrospective epidemiological study of swine populations in China, we describe novel lineages of porcine hemagglutinating encephalomyelitis virus (PHEV) complex coronaviruses (CoVs) that cause exclusively respiratory symptoms with no signs of the neurological symptoms typically associated with classical PHEV infection. Through large-scale epidemiological surveillance, we show that these novel lineages have circulated in at least eight provinces in southeastern China. Phylogenetic and recombination analyses of twenty-four genomes identified two major viral lineages causing respiratory symptoms with extensive recombination within them, between them, and between classical PHEV and the novel respiratory variant PHEV (rvPHEV) lineages. Divergence times among the sampled lineages in the PHEV virus complex date back to 1886-1958 (mean estimate 1928), with the two major rvPHEV lineages separating approximately 20 years later. Many rvPHEV viruses show amino acid substitutions at the carbohydrate-binding site of hemagglutinin esterase (HE) and/or have lost the cysteine required for HE dimerization. This resembles the early adaptation of human CoVs, where HE lost its hemagglutination ability to adapt to growth in the human respiratory tract. Our study represents the first report of the evolutionary history of rvPHEV circulating in swine and highlights the importance of characterizing CoV diversity and recombination in swine to identify pathogens with outbreak potential that could threaten swine farming., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press.)

Increasing levels of artemisinin and partner drug resistance threaten malaria control and elimination globally. Triple artemisinin-based combination therapies (TACTs) which combine artemisinin derivatives with two partner drugs are efficacious and well tolerated in clinical trials, including in areas of multidrug-resistant malaria. Whether early TACT adoption could delay the emergence and spread of antimalarial drug resistance is a question of vital importance. Using two independent individual-based models of Plasmodium falciparum epidemiology and evolution, we evaluated whether introduction of either artesunate-mefloquine-piperaquine or artemether-lumefantrine-amodiaquine resulted in lower long-term artemisinin-resistance levels and treatment failure rates compared with continued ACT use. We show that introduction of TACTs could significantly delay the emergence and spread of artemisinin resistance and treatment failure, extending the useful therapeutic life of current antimalarial drugs, and improving the chances of malaria elimination. We conclude that immediate introduction of TACTs should be considered by policy makers in areas of emerging artemisinin resistance., (© 2023. The Author(s).)

Mass drug administration (MDA) with antimalarials has been shown to reduce prevalence and interrupt transmission in small populations, in populations with reliable access to antimalarial drugs, and in populations where sustained improvements in diagnosis and treatment are possible. In addition, when MDA is effective it eliminates both drug-resistant parasites and drug-sensitive parasites, which has the long-term benefit of extending the useful therapeutic life of first-line therapies for all populations, not just the focal population where MDA was carried out. However, in order to plan elimination measures effectively, it is necessary to characterize the conditions under which failed MDA could exacerbate resistance. We use an individual-based stochastic model of Plasmodium falciparum transmission to evaluate this risk for MDA using dihydroartemisinin-piperaquine (DHA-PPQ), in populations where access to antimalarial treatments may not be uniformly high and where re-importation of drug-resistant parasites may be common. We find that artemisinin-resistance evolution at the kelch13 locus can be accelerated by MDA when all three of the following conditions are met: (1) strong genetic bottlenecking that falls short of elimination, (2) re-importation of artemisinin-resistant genotypes, and (3) continued selection pressure during routine case management post-MDA. Accelerated resistance levels are not immediate but follow the rebound of malaria cases post-MDA, if this is allowed to occur. Crucially, resistance is driven by the selection pressure during routine case management post-MDA and not the selection pressure exerted during the MDA itself. Second, we find that increasing treatment coverage post-MDA increases the probability of local elimination in low-transmission regions (prevalence < 2%) in scenarios with both low and high levels of drug-resistance importation. This emphasizes the importance of planning for and supporting high coverage of diagnosis and treatment post-MDA., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Nguyen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Much of the world experiences influenza in yearly recurring seasons, particularly in temperate areas. These patterns can be considered repeatable if they occur predictably and consistently at the same time of year. In tropical areas, including southeast Asia, timing of influenza epidemics is less consistent, leading to a lack of consensus regarding whether influenza is repeatable. This study aimed to assess repeatability of influenza in Vietnam, with repeatability defined as seasonality that occurs at a consistent time of year with low variation. We developed a mathematical model incorporating parameters to represent periods of increased transmission and then fitted the model to data collected from sentinel hospitals throughout Vietnam as well as four temperate locations. We fitted the model for individual (sub)types of influenza as well as all combined influenza throughout northern, central, and southern Vietnam. Repeatability was evaluated through the variance of the timings of peak transmission. Model fits from Vietnam show high variance (sd = 64-179 days) in peak transmission timing, with peaks occurring at irregular intervals and throughout different times of year. Fits from temperate locations showed regular, annual epidemics in winter months, with low variance in peak timings (sd = 32-57 days). This suggests that influenza patterns are not repeatable or seasonal in Vietnam. Influenza prevention in Vietnam therefore cannot rely on anticipation of regularly occurring outbreaks., Competing Interests: The authors declare that they have no competing interests., (Copyright: © 2023 Servadio et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Nowadays, the ability to make data-driven decisions in public health is of utmost importance. To achieve this, it is necessary for modelers to comprehend the impact of models on the future state of healthcare systems. Compartmental models are a valuable tool for making informed epidemiological decisions, and the proper parameterization of these models is crucial for analyzing epidemiological events. This work evaluated the use of compartmental models in conjunction with Particle Swarm Optimization (PSO) to determine optimal solutions and understand the dynamics of Dengue epidemics. The focus was on calculating and evaluating the rate of case reproduction, R 0 , for the Republic of Panama. Three compartmental models were compared: Susceptible-Infected-Recovered (SIR), Susceptible-Exposed-Infected-Recovered (SEIR), and Susceptible-Infected-Recovered Human-Susceptible-Infected Vector (SIR Human-SI Vector, SIR-SI). The models were informed by demographic data and Dengue incidence in the Republic of Panama between 1999 and 2022, and the susceptible population was analyzed. The SIR, SEIR, and SIR-SI models successfully provided R 0 estimates ranging from 1.09 to 1.74. This study provides, to the best of our understanding, the first calculation of R 0 for Dengue outbreaks in the Republic of Panama., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Disease emergence in livestock is a product of environment, epidemiology and economic forces. The environmental factors contributing to novel pathogen emergence in humans have been studied extensively, but the two-way relationship between farm microeconomics and outbreak risk has received comparably little attention. We introduce a game-theoretic model where farmers produce and sell two goods, one of which (e.g. pigs, poultry) is susceptible to infection by a pathogen. We model market and epidemiological effects at both the individual farm level and the community level. We find that in the case of low demand elasticity for livestock meat, the presence of an animal pathogen causing production losses can lead to a bistable system where two outcomes are possible: (i) successful disease control or (ii) maintained disease circulation, where farmers slaughter their animals at a low rate, face substantial production losses, but maintain large herds because of the appeal of high meat prices. Our observations point to the potentially critical effect of price elasticity of demand for livestock products on the success or failure of livestock disease control policies. We show the potential epidemiological benefits of (i) policies aimed at stabilizing livestock product prices, (ii) subsidies for alternative agricultural activities during epidemics, and (iii) diversifying agricultural production and sources of proteins available to consumers., (© 2023 The Authors.)

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 MalariaGEN et al.)

Malaria due to the Plasmodium falciparum parasite remains a threat to human health despite eradication efforts and the development of anti-malarial treatments, such as artemisinin combination therapies. Human movement and migration have been linked to the propagation of malaria on national scales, highlighting the need for the incorporation of human movement in modeling efforts. Spatially couped individual-based models have been used to study how anti-malarial resistance evolves and spreads in response to drug policy changes; however, as the spatial scale of the model increases, the challenges associated with modeling of movement also increase. In this paper we discuss the development, calibration, and validation of a movement model in the context of a national-scale, spatial, individual-based model used to study the evolution of drug resistance in the malaria parasite., (© 2023. The Author(s).)

Treatment of symptomatic malaria became a routine component of the clinical and public health response to malaria after the second world war. However, all antimalarial drugs deployed against malaria eventually generated enough drug resistance that they had to be removed from use. Chloroquine, sulfadoxine-pyrimethamine, and mefloquine are well known examples of antimalarial drugs to which resistance did and still does ready evolve. Artemisinin-based combination therapies (ACTs) are currently facing the same challenge as artemisinin resistance is widespread in Southeast Asia and emerging in Africa. Here, I review some aspects of drug-resistance management in malaria that influence the strength of selective pressure on drug-resistant malaria parasites, as well as an approach we can take in the future to avoid repeating the common mistake of deploying a new drug and waiting for drug resistance and treatment failure to arrive. A desirable goal of drug-resistance management is to reduce selection pressure without reducing the overall percentage of patients that are treated. This can be achieved by distributing multiple first-line therapies (MFT) simultaneously in the population for the treatment of uncomplicated falciparum malaria, thereby keeping treatment levels high but the overall selection pressure exerted by each individual therapy low. I review the primary reasons that make MFT a preferred resistance management option in many malaria-endemic settings, and I describe two exceptions where caution and additional analyses may be warranted before deploying MFT. MFT has shown to be feasible in practice in many endemic settings. The continual improvement and increased coverage of genomic surveillance in malaria may allow countries to implement custom MFT strategies based on their current drug-resistance profiles., 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., (© 2022 Boni.)