Distribution of clones among hosts for the lizard malaria parasite Plasmodium mexicanum

Drought correlates with reduced infection complexity and possibly prevalence in a decades-long study of the lizard malaria parasite Plasmodium mexicanum

Microparasites often exist as a collection of genetic 'clones' within a single host (termed multi-clonal, or complex, infections). Malaria parasites are no exception, with complex infections playing key roles in parasite ecology. Even so, we know little about what factors govern the distribution and abundance of complex infections in natural settings. Utilizing a natural dataset that spans more than 20 years, we examined the effects of drought conditions on infection complexity and prevalence in the lizard malaria parasite Plasmodium mexicanum and its vertebrate host, the western fence lizard, Sceloporus occidentalis. We analyzed data for 14,011 lizards sampled from ten sites over 34 years with an average infection rate of 16.2%. Infection complexity was assessed for 546 infected lizards sampled during the most recent 20 years. Our data illustrate significant, negative effects of drought-like conditions on infection complexity, with infection complexity expected to increase by a factor of 2.27 from the lowest to highest rainfall years. The relationship between rainfall and parasite prevalence is somewhat more ambiguous; when prevalence is modeled over the full range in years, a 50% increase in prevalence is predicted between the lowest and highest rainfall years, but this trend is not apparent or is reversed when data are analyzed over a shorter timeframe. To our knowledge, this is the first reported evidence for drought affecting the abundance of multi-clonal infections in malaria parasites. It is not yet clear what mechanism might connect drought with infection complexity, but the correlation we observed suggests that additional research on how drought influences parasite features like infection complexity, transmission rates and within-host competition may be worthwhile.

A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data

The introduction of genomic methods facilitated standardized molecular disease surveillance. For instance, SNP barcodes in Plasmodium vivax and Plasmodium falciparum malaria allows the characterization of haplotypes, their frequencies and prevalence to reveal temporal and spatial transmission patterns. A confounding factor is the presence of multiple genetically distinct pathogen variants within the same infection, known as multiplicity of infection (MOI). Disregarding ambiguous information, as usually done in ad-hoc approaches, leads to less confident and biased estimates. We introduce a statistical framework to obtain maximum-likelihood estimates (MLE) of haplotype frequencies and prevalence alongside MOI from malaria SNP data, i.e., multiple biallelic marker loci. The number of model parameters increases geometrically with the number of genetic markers considered and no closed-form solution exists for the MLE. Therefore, the MLE needs to be derived numerically. We use the Expectation-Maximization (EM) algorithm to derive the maximum-likelihood estimates, an efficient and easy-to-implement algorithm that yields a numerically stable solution. We also derive expressions for haplotype prevalence based on either all or just the unambiguous genetic information and compare both approaches. The latter corresponds to a biased ad-hoc estimate of prevalence. We assess the performance of our estimator by systematic numerical simulations assuming realistic sample sizes and various scenarios of transmission intensity. For reasonable sample sizes, and number of loci, the method has little bias. As an example, we apply the method to a dataset from Cameroon on sulfadoxine-pyrimethamine resistance in P. falciparum malaria. The method is not confined to malaria and can be applied to any infectious disease with similar transmission behavior. An easy-to-use implementation of the method as an R-script is provided.