Robustness of the reproductive number estimates in vector-borne disease systems

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: All relevant data are within the paper and its Supporting Information files.Background: The required efforts, feasibility and predicted success of an intervention strategy against an infectious disease are partially determined by its basic reproduction number, R0. In its simplest form R0 can be understood as the product of the infectious period, the number of infectious contacts and the per-contact transmission probability, which in the case of vector-transmitted diseases necessarily extend to the vector stages. As vectors do not usually recover from infection, they remain infectious for life, which places high significance on the vector’s life expectancy. Current methods for estimating the R0 for a vector-borne disease are mostly derived from compartmental modelling frameworks assuming constant vector mortality rates. We hypothesised that some of the assumptions underlying these models can lead to unrealistic high vector life expectancies with important repercussions for R0 estimates. Methodology and principal findings: Here we used a stochastic, individual-based model which allowed us to directly measure the number of secondary infections arising from one index case under different assumptions about vector mortality. Our results confirm that formulas based on age-independent mortality rates can overestimate R0 by nearly 100% compared to our own estimate derived from first principles. We further provide a correction factor that can be used with a standard R0 formula and adjusts for the discrepancies due to erroneous vector age distributions. Conclusion: Vector mortality rates play a crucial role for the success and general epidemiology of vector-transmitted diseases. Many modelling efforts intrinsically assume these to be age-independent, which, as clearly demonstrated here, can lead to severe over-estimation of the disease’s reproduction number. Our results thus re-emphasise the importance of obtaining field-relevant and species-dependent vector mortality rates, which in turn would facilitate more realistic intervention impact predictions.Engineering and Physical Sciences Research Council (EPSRC

Recent advances in the molecular epidemiology of clinical malaria

This is the final version of the article. Available from the publisher via the DOI in this record.Human malaria is a complex disease that can show a wide array of clinical outcomes, from asymptomatic carriage and chronic infection to acute disease presenting various life-threatening pathologies. The specific outcome of an infection is believed to be determined by a multifactorial interplay between the host and the parasite but with a general trend toward disease attenuation with increasing prior exposure. Therefore, the main burden of malaria in a population can be understood as a function of transmission intensity, which itself is intricately linked to the prevalence of infected hosts and mosquito vectors, the distribution of infection outcomes, and the parasite population diversity. Predicting the long-term impact of malaria intervention measures therefore requires an in-depth understanding of how the parasite causes disease, how this relates to previous exposures, and how different infection pathologies contribute to parasite transmission. Here, we provide a brief overview of recent advances in the molecular epidemiology of clinical malaria and how these might prove to be influential in our fight against this important disease.MR is supported by the Medical Research Council (grant MR/M003906/1)

Multiscale Immune Selection and the Transmission-Diversity Feedback in Antigenically Diverse Pathogen Systems

This is the final version of the article. Available from University of Chicago Press via the DOI in this record.Antigenic diversity is commonly used by pathogens to enhance their transmission success. Within-host clonal antigenic variation helps to maintain long infectious periods, whereas high levels of allelic diversity at the population level significantly expand the pool of susceptible individuals. Diversity, however, is not necessarily a static property of a pathogen population but in many cases is generated by the very act of infection and transmission, and it is therefore expected to respond dynamically to changes in transmission and immune selection. We hypothesized that this coupling creates a positive feedback whereby infection and disease transmission promote the generation of diversity, which itself facilitates immune evasion and further infections. To investigate this link in more detail, we considered the human malaria parasite Plasmodium falciparum, one of the most important antigenically diverse pathogens. We developed an individual-based model in which antigenic diversity emerges as a dynamic property from the underlying transmission processes. Our results show that the balance between stochastic extinction and the generation of new antigenic variants is intrinsically linked to within-host and between-host immune selection. This in turn determines the level of diversity that can be maintained in a given population. Furthermore, the transmission-diversity feedback can lead to temporal lags in the response to natural or intervention-induced perturbations in transmission rates. Our results therefore have important implications for monitoring and assessing the effectiveness of disease control efforts

The effects of tertiary and quaternary infections on the epidemiology of dengue

This is the final version of the article. Available from Public Library of Science via the DOI in this record.The epidemiology of dengue is characterised by irregular epidemic outbreaks and desynchronised dynamics of its four co-circulating virus serotypes. Whilst infection by one serotype appears to convey life-long protection to homologous infection, it is believed to be a risk factor for severe disease manifestations upon secondary, heterologous infection due to the phenomenon of Antibody-Dependent Enhancement (ADE). Subsequent clinical infections are rarely reported and, since the majority of dengue infections are generally asymptomatic, it is not clear if and to what degree tertiary or quaternary infections contribute to dengue epidemiology. Here we investigate the effect of third and subsequent infections on the transmission dynamics of dengue and show that although the qualitative patterns are largely equivalent, the system more readily exhibits the desynchronised serotype oscillations and multi-annual epidemic outbreaks upon their inclusion. More importantly, permitting third and fourth infections significantly increases the force of infection without resorting to high basic reproductive numbers. Realistic age-prevalent patterns and seroconversion rates are therefore easier reconciled with a low value of dengue's transmission potential if allowing for more than two infections; this should have important consequences for dengue control and intervention measures.This work was funded by the BBSRC (PSW) and the Royal Society (MR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

The effects of symmetry on the dynamics of antigenic variation

In the studies of dynamics of pathogens and their interactions with a host immune system, an important role is played by the structure of antigenic variants associated with a pathogen. Using the example of a model of antigenic variation in malaria, we show how many of the observed dynamical regimes can be explained in terms of the symmetry of interactions between different antigenic variants. The results of this analysis are quite generic, and have wider implications for understanding the dynamics of immune escape of other parasites, as well as for the dynamics of multi-strain diseases.Comment: 21 pages, 4 figures; J. Math. Biol. (2012), Online Firs

The Socio-Technical Dimension of Inertia in Digital Transformations

When organizations undertake large transformation initiatives enabled by information technology, these efforts are often hampered by inertia. The literature suggests that inertia plays a dual role in organizations: it is both required for organizational efficiency and an antecedent of resistance to change. While traditionally inertia is believed to reside in human actors, we suggest that inertia is rooted in multiple facets – in routines, resources such as social agents, and also technology – and plays on multiple levels – at individual, group, and organizational ones. In this essay, we propose a new conceptualization of inertia that encompasses and integrates these elements. Our model suggests that inertia occurs as path-dependent rigidity in organizational behavior through the coalescence of social entities with technology artifacts. We illustrate our new understanding of inertia by revisiting two case vignettes of inertia and impeded digital transformations

Intralocus sexual conflict can resolve the male-female health-survival paradox

This is the final version. Available on open access from Springer Nature via the DOI in this recordAt any given age, men are more likely to die than women, but women have poorer health at older ages. This is referred to as the “male-female, health-survival paradox”, which is not fully understood. Here, we provide a general solution to the paradox that relies on intralocus sexual conflict, where alleles segregating in the population have late-acting positive effects on male fitness, but negative effects on female health. Using an evolutionary modelling framework we show that male-benefit, female-detriment alleles can spread if they are expressed after female reproduction stops. We provide support for our conflict based solution using experimental Drosophila data. Our results show that selecting for increased late-life male reproductive effort can increase male fitness but have a detrimental effect on female fitness. Furthermore, we show that late-life male fertility is negatively genetically correlated with female health. Our study suggests that intralocus sexual conflict could resolve the health-survival paradoxWe thank the National Science Center (Poland: 2013/09/N/NZ/NZ8/03231) and the Leverhulme Trust (UK: RF-2015-01) for funding which partially supported this work, and the University of Exeter’s Dean’s Fellowship for additional support

Assessing dengue vaccination impact: Model challenges and future directions.

In response to the sharp rise in the global burden caused by dengue virus (DENV) over the last few decades, the WHO has set out three specific key objectives in its disease control strategy: (i) to estimate the true burden of dengue by 2015; (ii) a reduction in dengue mortality by at least 50% by 2020 (used as a baseline); and (iii) a reduction in dengue morbidity by at least 25% by 2020. Although various elements will all play crucial parts in achieving this goal, from diagnosis and case management to integrated surveillance and outbreak response, sustainable vector control, vaccine implementation and finally operational and implementation research, it seems clear that new tools (e.g. a safe and effective vaccine and/or effective vector control) are key to success. The first dengue vaccine was licensed in December 2015, Dengvaxia® (CYD-TDV) developed by Sanofi Pasteur. The WHO has provided guidance on the use of CYD-TDV in endemic countries, for which there are a variety of considerations beyond the risk-benefit evaluation done by regulatory authorities, including public health impact and cost-effectiveness. Population-level vaccine impact and economic and financial aspects are two issues that can potentially be considered by means of mathematical modelling, especially for new products for which empirical data are still lacking. In December 2014 a meeting was convened by the WHO in order to revisit the current status of dengue transmission models and their utility for public health decision-making. Here, we report on the main points of discussion and the conclusions of this meeting, as well as next steps for maximising the use of mathematical models for vaccine decision-making