Breaking the cycle of malaria treatment failure

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

Traits, habitats, and clades: Identifying traits of potential importance to environmental filtering

Environmental filtering is a fundamental process in the ecological assembly of communities. Recently developed phylogenetic tools identify patterns associated with environmental filtering across whole communities. Here we introduce a novel method that allows the detection of traits involved in the environmental filtering of species from specific clades in specific habitat types. Our approach identifies nonindependent trait/habitat/clade (THC) associations and also provides a framework for detecting clearly defined two‐way trait/clade, trait/habitat, and clade/habitat associations. The THC method relies on exact binomial tests and differentiates THC associations resulting from a three‐way interaction from those that are generated by one or more underlying significant two‐way interactions. It can also detect THC associations for which there are no significant two‐way associations (trait/habitat, trait/clade, clade/habitat). To illustrate the THC method, we examine plant pollination and dispersal traits from six habitat types in a fragmented Costa Rican landscape. Results suggest that these traits are not widely important for the environmental filtering of most clades in this landscape, but animal dispersal and insect pollination are involved in the filtering of monocots and the Piperaceae in rain forest understory

Mathematical Models for a New Era of Malaria Eradication

Maciej Boni and colleagues discuss a new model exploring how a switch in antimalarial drug use to artemisinin-based combination therapies will affect malaria prevalence and incidence in endemic regions

Influenza vaccine allocation in tropical settings under constrained resources

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

Clinically immune hosts as a refuge for drug-sensitive malaria parasites

<p>Abstract</p> <p>Background</p> <p>Mutations in <it>Plasmodium falciparum </it>that confer resistance to first-line antimalarial drugs have spread throughout the world from a few independent foci, all located in areas that were likely characterized by low or unstable malaria transmission. One of the striking differences between areas of low or unstable malaria transmission and hyperendemic areas is the difference in the size of the population of immune individuals. However, epidemiological models of malaria transmission have generally ignored the role of immune individuals in transmission, assuming that they do not affect the fitness of the parasite. This model reconsiders the role of immunity in the dynamics of malaria transmission and its impact on the evolution of antimalarial drug resistance under the assumption that immune individuals are infectious.</p> <p>Methods</p> <p>The model is constructed as a two-stage susceptible-infected-susceptible (SIS) model of malaria transmission that assumes that individuals build up clinical immunity over a period of years. This immunity reduces the frequency and severity of clinical symptoms, and thus their use of drugs. It also reduces an individual's level of infectiousness, but does not impact the likelihood of becoming infected.</p> <p>Results</p> <p>Simulations found that with the introduction of resistance into a population, clinical immunity can significantly alter the fitness of the resistant parasite, and thereby impact the ability of the resistant parasite to spread from an initial host by reducing the effective reproductive number of the resistant parasite as transmission intensity increases. At high transmission levels, despite a higher basic reproductive number, <it>R</it>₀, the effective reproductive number of the resistant parasite may fall below the reproductive number of the sensitive parasite.</p> <p>Conclusion</p> <p>These results suggest that high-levels of clinical immunity create a natural ecological refuge for drug-sensitive parasites. This provides an epidemiological rationale for historical patterns of resistance emergence and suggests that future outbreaks of resistance are more likely to occur in low- or unstable-transmission settings. This finding has implications for the design of drug policies and the formulation of malaria control strategies, especially those that lower malaria transmission intensity.</p

Guidelines for Identifying Homologous Recombination Events in Influenza A Virus

The rapid evolution of influenza viruses occurs both clonally and non-clonally through a variety of genetic mechanisms and selection pressures. The non-clonal evolution of influenza viruses comprises relatively frequent reassortment among gene segments and a more rarely reported process of non-homologous RNA recombination. Homologous RNA recombination within segments has been proposed as a third such mechanism, but to date the evidence for the existence of this process among influenza viruses has been both weak and controversial. As homologous recombination has not yet been demonstrated in the laboratory, supporting evidence, if it exists, may come primarily from patterns of phylogenetic incongruence observed in gene sequence data. Here, we review the necessary criteria related to laboratory procedures and sample handling, bioinformatic analysis, and the known ecology and evolution of influenza viruses that need to be met in order to confirm that a homologous recombination event occurred in the history of a set of sequences. To determine if these criteria have an effect on recombination analysis, we gathered 8307 publicly available full-length sequences of influenza A segments and divided them into those that were sequenced via the National Institutes of Health Influenza Genome Sequencing Project (IGSP) and those that were not. As sample handling and sequencing are executed to a very high standard in the IGSP, these sequences should be less likely to be exposed to contamination by other samples or by laboratory strains, and thus should not exhibit laboratory-generated signals of homologous recombination. Our analysis shows that the IGSP data set contains only two phylogenetically-supported single recombinant sequences and no recombinant clades. In marked contrast, the non-IGSP data show a very large amount of potential recombination. We conclude that the presence of false positive signals in the non-IGSP data is more likely than false negatives in the IGSP data, and that given the evidence to date, homologous recombination seems to play little or no role in the evolution of influenza A viruses

The prevalences of Salmonella Genomic Island 1 variants in human and animal Salmonella Typhimurium DT104 are distinguishable using a Bayesian approach

Throughout the 1990s, there was an epidemic of multidrug resistant Salmonella Typhimurium DT104 in both animals and humans in Scotland. The use of antimicrobials in agriculture is often cited as a major source of antimicrobial resistance in pathogenic bacteria of humans, suggesting that DT104 in animals and humans should demonstrate similar prevalences of resistance determinants. Until very recently, only the application of molecular methods would allow such a comparison and our understanding has been hindered by the fact that surveillance data are primarily phenotypic in nature. Here, using large scale surveillance datasets and a novel Bayesian approach, we infer and compare the prevalence of Salmonella Genomic Island 1 (SGI1), SGI1 variants, and resistance determinants independent of SGI1 in animal and human DT104 isolates from such phenotypic data. We demonstrate differences in the prevalences of SGI1, SGI1-B, SGI1-C, absence of SGI1, and tetracycline resistance determinants independent of SGI1 between these human and animal populations, a finding that challenges established tenets that DT104 in domestic animals and humans are from the same well-mixed microbial population