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Parasite drug resistance presents a major obstacle to controlling and eliminating vector-borne diseases affecting humans and animals. While vector-borne disease dynamics are affected by factors related to parasite, vertebrate host and vector, research on drug resistance in filarial parasites has primarily focused on the parasite and vertebrate host, rather than the mosquito. However, we expect that the physiological costs associated with drug resistance would reduce the fitness of drug-resistant vs. drug-susceptible parasites in the mosquito wherein parasites are not exposed to drugs. Here we test this hypothesis using four isolates of the dog heartworm (Dirofilaria immitis)&mdash, two drug susceptible and two drug resistant&mdash, and two vectors&mdash, the yellow fever mosquito (Aedes aegypti) and the Asian tiger mosquito (Ae. albopictus)&mdash, as our model system. Our data indicated that while vector species had a significant effect on vectorial capacity, there was no significant difference in the vectorial capacity of mosquitoes infected with drug-resistant vs. drug-susceptible parasites. Consequently, contrary to expectations, our data indicate that drug resistance in D. immitis does not appear to reduce the transmission efficiency of these parasites, and thus the spread of drug-resistant parasites in the vertebrate population is unlikely to be mitigated by reduced fitness in the mosquito vector.

Aim: Macroecological analyses provide valuable insights into factors that influence how parasites are distributed across space and among hosts. Amid large uncertainties that arise when generalizing from local and regional findings, hierarchical approaches applied to global datasets are required to determine whether drivers of parasite infection patterns vary across scales. We assessed global patterns of haemosporidian infections across a broad diversity of avian host clades and zoogeographical realms to depict hotspots of prevalence and to identify possible underlying drivers. Location: Global. Time period: 1994–2019. Major taxa studied: Avian haemosporidian parasites (genera Plasmodium, Haemoproteus, Leucocytozoon and Parahaemoproteus). Methods: We amalgamated infection data from 53,669 individual birds representing 2,445 species world-wide. Spatio-phylogenetic hierarchical Bayesian models were built to disentangle potential landscape, climatic and biotic drivers of infection probability while accounting for spatial context and avian host phylogenetic relationships. Results: Idiosyncratic responses of the three most common haemosporidian genera to climate, habitat, host relatedness and host ecological traits indicated marked variation in host infection rates from local to global scales. Notably, host ecological drivers, such as migration distance for Plasmodium and Parahaemoproteus, exhibited predominantly varying or even opposite effects on infection rates across regions, whereas climatic effects on infection rates were more consistent across realms. Moreover, infections in some low-prevalence realms were disproportionately concentrated in a few local hotspots, suggesting that regional-scale variation in habitat and microclimate might influence transmission, in addition to global drivers. Main conclusions: Our hierarchical global analysis supports regional-scale findings showing the synergistic effects of landscape, climate and host ecological traits on parasite transmission for a cosmopolitan and diverse group of avian parasites. Our results underscore the need to account for such interactions, in addition to possible variation in drivers across regions, to produce the robust inference required to predict changes in infection risk under future scenarios.

Researchers worldwide are repeatedly warning us against future zoonotic diseases resulting from humankind’s insurgence into natural ecosystems. The same zoonotic pathogens that cause severe infections in a human host frequently fail to produce any disease outcome in their natural hosts. What precise features of the immune system enable natural reservoirs to carry these pathogens so efficiently? To understand these effects, we highlight the importance of tracing the evolutionary basis of pathogen tolerance in reservoir hosts, while drawing implications from their diverse physiological and life-history traits, and ecological contexts of host-pathogen interactions. Long-term co-evolution might allow reservoir hosts to modulate immunity and evolve tolerance to zoonotic pathogens, increasing their circulation and infectious period. Such processes can also create a genetically diverse pathogen pool by allowing more mutations and genetic exchanges between circulating strains, thereby harboring rare alive-on-arrival variants with extended infectivity to new hosts (i.e., spillover). Finally, we end by underscoring the indispensability of a large multidisciplinary empirical framework to explore the proposed link between evolved tolerance, pathogen prevalence, and spillover in the wild.

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has been characterized by unprecedented rates of spatio-temporal spread. Here, we summarize the main events in the pandemic's timeline and evaluate what has been learnt by the public health community. We also discuss the implications for future public health policy and, specifically, the practice of epidemic control. We critically analyze this ongoing pandemic's timeline and contrast it with the 2002–2003 SARS outbreak. We identify specific areas (e.g., pathogen identification and initial reporting) wherein the international community learnt valuable lessons from the SARS outbreak. However, we also identify the key areas where international public health policy failed leading to the exponential spread of the pandemic. We outline a clear agenda for improved pandemic control in the future.

International audience; In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radio- logical fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem at- tributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This paper is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensi- tive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that ra- diological risk assessments must be designed and informed by rigorous statistical frameworks capable of reveal- ing the causal inference tying radiological exposure to the endpoints selected for measurement.

The spatial aggregation of related individuals can affect disease dynamics by altering contact rates between individuals and/or groups of individuals. However, kin-structure likely affects contact rates in a scale-dependent manner: increasing contact rates within, but decreasing contact rates amongst spatial groups. Thus, the effect of kin-structure on disease exposure risk should depend upon the spatial scale relevant for pathogen transmission. This study was undertaken to test the effects of kin-structure on disease dynamics in raccoons (Procyon lotor) inhabiting a highly fragmented agricultural ecosystem. Raccoons (n = 566) were trapped at 31 spatially discrete habitat patches (local populations). Trapped individuals were genotyped at 13 microsatellites and their serum screened for antibodies to canine distemper virus (CDV) and multiple Leptospira spp. serovars. Our analyses revealed that the effects of kin-structure on transmission dynamics are dependent on both spatial scale and the pathogen under consideration. Thus, in the directly transmitted pathogen (CDV), the probability of pathogen co-exposure (the proportion of individual pairs where both individuals were seropositive for a particular pathogen) was positively correlated with genealogical proximity within local populations. Conversely, in the environmentally transmitted leptospires co-exposure was homogeneous within local populations and was positively correlated with gene flow among these populations. Our analyses also revealed that, after controlling for confounding effects of landscape and demographic variables, the effects of kin-structure on disease exposure risk was pathogen-specific. In particular, increasing kin-structure was associated with increased disease exposure risk in the directly transmitted pathogen (CDV), and alternatively with decreased disease exposure risk in environmentally transmitted leptospires. The potential, scale-dependent, effects of kin-structure on disease exposure risk revealed by our analyses could play an important role in elucidating disease dynamics in natural populations and in planning effective disease mitigation strategies.

Traditional methods for characterizing genetic differentiation among populations rely on a priori grouping of individuals. Bayesian clustering methods avoid this limitation by using linkage and Hardy–Weinberg disequilibrium to decompose a sample of individuals into genetically distinct groups. There are several software programs available for Bayesian clustering analyses, all of which describe a decrease in the ability to detect distinct clusters as levels of genetic differentiation among populations decrease. However, no study has yet compared the performance of such methods at low levels of population differentiation, which may be common in species where populations have experienced recent separation or high levels of gene flow. We used simulated data to evaluate the performance of three Bayesian clustering software programs, PARTITION, STRUCTURE, and BAPS, at levels of population differentiation below FST=0.1. PARTITION was unable to correctly identify the number of subpopulations until levels of FST reached around 0.09. Both STRUCTURE and BAPS performed very well at low levels of population differentiation, and were able to correctly identify the number of subpopulations at FST around 0.03. The average proportion of an individual’s genome assigned to its true population of origin increased with increasing FST for both programs, reaching over 92% at an FST of 0.05. The average number of misassignments (assignments to the incorrect subpopulation) continued to decrease as FST increased, and when FST was 0.05, fewer than 3% of individuals were misassigned using either program. Both STRUCTURE and BAPS worked extremely well for inferring the number of clusters when clusters were not well-differentiated (FST=0.02–0.03), but our results suggest that FST must be at least 0.05 to reach an assignment accuracy of greater than 97%.

Leptospirosis is a globally important zoonotic disease occurring clinically and subclinically in humans and animals.To determine whether raccoons in Indiana carried leptospires in their kidneys.Thirty-four raccoons were live-trapped from two forest patches in central Indiana. Following euthanasia, a portion of kidney (2 cm(2)) from each raccoon was homogenized and used for leptospiral culture. Leptospiral cultures were subjected to DNA extraction and various polymerase chain reaction (PCR) procedures reported previously. Serum sample from each raccoon was collected and antibody titers to leptospiral serovars were determined by microscopic agglutination test (MAT).All leptospiral cultures were positive for Leptospira by various PCR procedures. The PCR with the primers targeting the conservative region of LipL32 gene was the most sensitive PCR in the detection of pathogenic leptospires. The variable LipL32 PCR amplicons were sequenced and compared to the reference strains available in GenBank. Twelve kidney cultures had Leptospira interrogans, eight had Leptospira kirschneri and two had Leptospira borgpetersenii. They were predominantly Grippotyphosa serogroup. Antileptospire antibodies were detected in 16 out of 34 raccoons (47.1%) by MAT. There were titers ≥ 1:80 in 16 raccoons (47.1%) and titers ≥ 1:400 in 3 raccoons (8.8%). The highest leptospiral serovar-specific seroreactivity among 34 raccoons was L. interrogans Bratislava (38.2%) and L. interrogans Grippotyphosa (32.4%).Raccoons in Indiana carry leptospiral organisms in kidneys and the leptospires are predominantly L. interrogans species and of the Grippotyphosa serogroup.The raccoons serve as reservoir hosts that exposure sources to wildlife, livestock, pets and humans.

The objective of this study was to characterize the antibody prevalence of important livestock and domestic animal pathogens in raccoons (Procyon lotor) trapped and sampled in 39 forest patches in north-central Indiana, USA, between 2004 and 2005. A total of 459 serum samples were tested for antibodies to Leptospira serovars, 512 for Canine distemper virus (CDV) antibodies, and 340 for antibodies to Porcine reproductive and respiratory syndrome virus (PRRSV). In total, 47, 16, and 0% of the samples were seropositive for at least one Leptospira serovar, CDV, and PRRSV, respectively. Most of the positive Leptospira results were to serovars grippotyphosa (36%), autumnalis (22%), and hardjo (22%). No statistically significant correlation was found between antibody prevalence estimates for different Leptospira serovars. A significant association was found between body weight and antibodies for Leptospira serovars and CDV. In addition, age (adult vs. juvenile) was significantly associated with the presence of CDV antibody, with adults exhibiting a higher prevalence than juveniles. This study confirmed that raccoons in Indiana, USA, are exposed to different Leptospira interrogans serovars and CDV and that age and weight are associated with the presence of antibodies for both pathogens.