Theory predicts that selection for pathogen virulence and horizontal transmission is highest at the onset of an epidemic but decreases thereafter, as the epidemic depletes the pool of susceptible hosts. We tested this prediction by tracking the competition between the latent bacteriophage λ and its virulent mutant λcI857 throughout experimental epidemics taking place in continuous cultures of Escherichia coli. As expected, the virulent λcI857 is strongly favored in the early stage of the epidemic, but loses competition with the latent virus as prevalence increases. We show that the observed transient selection for virulence and horizontal transmission can be fully explained within the framework of evolutionary epidemiology theory. This experimental validation of our predictions is a key step towards a predictive theory for the evolution of virulence in emerging infectious diseases.

Mixed-genotype parasite infections are common in nature. Theoretical studies analyze the effects of such infections over evolutionary time and predict an increase in virulence due to the competitive advantage of virulent parasites. In contrast, experimental studies compare the overall virulence of mixed and single infections within one generation. Although these within-generation comparisons have limited relevance to existing theory, they demonstrate that within-host parasite interactions are not restricted to competition for resources, as envisaged by theory. Instead, mixed infections may result in phenotypic changes in growth rate or impaired immune clearance. Developing and using a two-parasite epidemiological model with recovery, we confirm that within-host competition for resources selects for higher virulence. However, parasite phenotypic plasticity and impaired host immunity can select for lower virulence. Because these latter two mechanisms would be detected by experimentalists as an increase in pathology, our results warn against the temptation to draw inferences on virulence evolution on the basis of single-generation experiments.

Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼10 7 km 2 . We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.is an arbovirus transmitted by Aedes mosquitos in the tropics and subtropics of the world. The virus causes an estimated 390 million infections per year, resulting in 96 million clinically symptomatic cases (1). DENV has four serotypes (DENV-1, DENV-2, DENV-3, and DENV-4) that each circulate worldwide. The spatial propagation of dengue transmission at short distances by the mosquito vector is well-understood, but the mechanism of long-distance spread has remained unclear. Disease transmission over large geographical distances is difficult to measure directly, but epidemiological coupling of locations revealed by synchrony in population-level disease patterns has been used successfully in the past to infer mechanisms of spread

In West Africa, lineage splitting between the M and S molecular forms of the major Afro-tropical malaria mosquito, Anopheles gambiae is thought to be driven by ecological divergence, occurring mainly at the larval stage. Here, we present evidences for habitat segregation between the two molecular forms in and around irrigated rice-fields located within the humid savannahs background of western Burkina Faso. Longitudinal sampling of adult mosquitoes emerging from a range of breeding sites distributed along a transect extending from the heart of the rice-fields area into the surrounding savannahs was conducted from June to November 2009. Analysis revealed that the two molecular forms and their sibling species An. arabiensis are not randomly distributed in the area. A major ecological gradient was extracted, in relation to the rice-fields perimeter. The M form was associated with larger breeding sites, which were mainly represented by rice field paddies whereas the S form and An. arabiensis were found to depend upon temporary, rain-filled breeding sites. These results support hypotheses about larval habitat segregation and confirm that both forms have different larval habitat requirement. Segregation appears clearly linked to anthropogenic permanent habitats and the community structure they support.

Since Dec 2019, the COVID-19 epidemic has spread over the globe creating one of the greatest pandemics ever witnessed. This epidemic wave will only begin to roll back once a critical proportion of the population is immunised, either by mounting natural immunity following infection, or by vaccination. The latter option can minimise the cost in terms of human lives but it requires to wait until a safe and efficient vaccine is developed, a period estimated to last at least 18 months. In this work, we use optimal control theory to explore the best strategy to implement while waiting for the vaccine. We seek a solution minimizing deaths and costs due to the implementation of the control strategy itself. We find that such a solution leads to an increasing level of control with a maximum reached near the fourth month of the epidemics and a steady decrease until vaccine deployment. This strategy strongly outperforms others with constant or cycling allocations of the same amount of resources to control the outbreak. This work opens new perspectives to mitigate the effects of the ongoing COVID-19 pandemics, and be used as a proof-of-concept in using mathematical modelling techniques to enlighten decision making and public health management in the early times of an outbreak.

Background Little is known about the natural history of asymptomatic SARS-CoV-2 infection or its contribution to infection transmission. Methods We conducted a prospective study at a quarantine center for COVID-19 in Ho Chi Minh City, Vietnam. We enrolled quarantined people with RT-PCR-confirmed SARS-CoV-2 infection, collecting clinical data, travel and contact history, and saliva at enrolment and daily nasopharyngeal throat swabs (NTS) for RT-PCR testing. We compared the natural history and transmission potential of asymptomatic and symptomatic individuals. Results Between March 10th and April 4th, 2020, 14,000 quarantined people were tested for SARS-CoV-2; 49 were positive. Of these, 30 participated in the study: 13(43%) never had symptoms and 17(57%) were symptomatic. 17(57%) participants acquired their infection outside Vietnam. Compared with symptomatic individuals, asymptomatic people were less likely to have detectable SARS-CoV-2 in NTS samples collected at enrolment (8/13 (62%) vs. 17/17 (100%) P=0.02). SARS-CoV-2 RNA was detected in 20/27 (74%) available saliva; 7/11 (64%) in the asymptomatic and 13/16 (81%) in the symptomatic group (P=0.56). Analysis of the probability of RT-PCR positivity showed asymptomatic participants had faster viral clearance than symptomatic participants (P<0.001 for difference over first 19 days). This difference was most pronounced during the first week of follow-up. Two of the asymptomatic individuals appeared to transmit the infection to up to four contacts. Conclusions Asymptomatic SARS-CoV-2 infection is common and can be detected by analysis of saliva or NTS. NTS viral loads fall faster in asymptomatic individuals, but they appear able to transmit the virus to others.

Theoretical studies of wildlife population dynamics have proved insightful for sustainable management, where the principal aim is to maximize short-term yield, without risking population extinction. Surprisingly, infectious diseases have not been accounted for in harvest models, which is a major oversight because the consequences of parasites for host population dynamics are well-established. Here, we present a simple general model for a host species subject to density dependent reproduction and seasonal demography. We assume this host species is subject to infection by a strongly immunizing, directly transmitted pathogen. In this context, we show that the interaction between density dependent effects and harvesting can substantially increase both disease prevalence and the absolute number of infectious individuals. This effect clearly increases the risk of cross-species disease transmission into domestic and livestock populations. In addition, if the disease is associated with a risk of mortality, then the synergistic interaction between hunting and disease-induced death can increase the probability of host population extinction.

Fourteen isolates of Rice yellow mottle virus (RYMV) were selected as representative of the genetic variability of the virus in Africa from a total set of 320 isolates serologically typed or partially sequenced. The 14 isolates were fully sequenced and analyzed together with two previously reported sequences. RYMV had a genomic organization similar to that of Cocksfoot mottle sobemovirus. The average nucleotide diversity among the 16 isolates of RYMV was 7%, and the maximum diversity between any two isolates was 10%. A strong conservative selection was apparent on both synonymous and nonsynonymous substitutions, through the amino acid replacement pattern, on the genome size, and through the limited number of indel events. Furthermore, there was a lack of positive selection on single amino acid sites and no evidence of recombination events. RYMV diversity had a pronounced and characteristic geographic structure. The branching order of the clades correlated with the geographic origin of the isolates along an east-to-west transect across Africa, and there was a marked decrease in nucleotide diversity moving westward across the continent. The insertion-deletion polymorphism was related to virus phylogeny. There was a partial phylogenetic incongruence between the coat protein gene and the rest of the genome. Overall, our results support the hypothesis that RYMV originated in East Africa and then dispersed and differentiated gradually from the east to the west of the continent.