1. Ecology and control of vectors
Vector-borne diseases are a globally important cause of human and animal disease that are particularly challenging to understand and manage because of their complex ecology. Moreover, resistance threatens to reverse progress made towards the control of multiple vector-borne diseases. Malaria is an archetypal example, where despite decades of efforts and considerable progress, transmission continues throughout much of Africa. Currently my main goal is to understand how we can exploit mosquito ecology to improve malaria control, specifically:
- Malaria mosquito population dynamics: Vector control remains the best way to reduce transmission; however, how different vector control tools, old: e.g. as long-lasting insecticidal treated bednets (LLINs) and anti-parasitic drug Ivermectin; or new: e.g. Olyset DUO nets; impact population dynamics and can lead to specific endpoints is largely unknown. I have been addressing this challenge by combining ecological modelling with surveillance data from multiple studies, including a clinical trial, that tackle different angles of malaria ecology. For example, see Viana et al. 2016. Main collaborators: Heather Ferguson, J. Matthiopoulos.
- Other projects include collaborations with Poppy Lamberton and Christina Faust to quantify the effects of drug treatments on life-history traits and trade-offs of drug-resistant Schistosoma mansoni (Viana et al 2017); and with Roman Biek and Caroline Millins on ecological community thresholds for tick-borne disease emergence, such as Lyme disease.
2. Disease reservoirs and cross-species transmission
Many important human, wildlife and livestock diseases infect multiple host species; however, in most cases only a subset of the hosts that can be infected are important for long-term pathogen persistence at the population level (i.e. the ‘reservoir’). Failure to understand which hosts constitute the infection reservoirs greatly undermines control strategies (Viana et al 2014). I have various ongoing projects to find ways to identify disease reservoirs, quantify cross-species transmission and determine their drivers, particularly of multi-host pathogens that infect wildlife. Some of these projects include:
- Canine viruses in the Serengeti: Three of the most prominent canine virus in the Serengeti: rabies virus, canine distemper virus (CDV) and canine parvovirus (CPV); are multi-host viruses. Although CPV and CDV are typically associated with domestic dogs, several outbreaks have been recorded in wild carnivores around the world. In the Serengeti, these are well known to infect lions and other wildlife.We’ve been using Bayesian state-space models to combine 30 years of CDV and CPV serological data in domestic dogs and lions from the Serengeti, to investigate the disease dynamics. We’re particularly interested in identifying the reservoir of infection, quantifying cross-species transmission and determining the role of vaccination on those dynamics. The CDV dynamics asfascinating (Viana et al 2015) but recently we started wondering about the importance of co-infection in this system and how vaccination might have impacted the patterns of CDV and CPV infection. Main collaborators: Abdelkader Behdenna, Sarah Cleaveland, Dan Haydon, Tiziana Lembo, Jason Matthiopoulos.
- Vampire bat viruses in Peru: Vampire bats are widespread throughout LatinAmerica and their range continues to expand due to intensification of livestock rearing, which provides a novel and abundant food resource. Their unique diet creates many opportunities for pathogen transmission from bats to livestock and humans. As a consequence, vampire bats are culled across much of Latin America, but the effects of culling on bat-associated pathogens are impossible to predict without better understanding of their natural transmission dynamics. I am working with the Streicker group on this system in Peru to develop approaches to determine the impact of bat culling on the dynamics of vampire bat rabies virus as well as exploring the transmission ecology of recently found bat influenza H17N10 and H18N11. Main collaborators: Daniel Streicker
- Brucellosis in Tanzania: Brucellosis is a bacterial zoonosis that has a worldwide distribution but human incidence is higher in low and mid-income countries. Tanzania is one such countries. We have been trying to understand the origins of human Brucella infections in Tanzania, which we know is transmitted from livestock but we don’t know from which animal host. After reconstructing Brucella transmission dynamics in northern Tanzania, our most recent hypothesis (Viana et al 2016) is that sheep and goats are the most likely source of human infections, challenging the paradigm that cattle are the main host that should be targeted for control. However, we still don’t know other fundamental aspects of transmission that are critical for control, for example, which Brucella species (B. abortus or B. melitensis) is responsible for human infection, the scale at which this is happening and if the source is the same regardless of this spatial scale. Main collaborators: Jo Halliday
- Other projects: I am lucky to be involved in other projects, including a really interesting collaboration with Pablo Murcia on Avian and Equine Influenza transmission among Mongolian horses.
3. Data, data, data….
I am fascinated by data that can tell a story, the larger and messier, the better. So I take any opportunity I get to try make sense of the data that is presented to me. In addition to infectious diseases, I am interested in most areas of quantitative ecology, and work (or have worked) on a series of other research themes, including:
Although I now focus on infectious diseases, I did my PhD on fisheries modelling. Fishing is central to the livelihood and food security of millions of people around the world. However, the removal of organisms from the marine ecosystem can greatly impact the biodiversity, stability and productivity of the ecosystems. I am interested in understanding these impacts and ﬁnding ways to maintain ﬁshing sustainable.
Since approximately 8% of the world total catch is discarded (with +60% discarding rate being common in certain fisheries) and the mortality rate of discarded organisms is very high, often approaching 100%, I focus in understanding how we can mitigate discards. Particularly, I use statistical modelling to understand 1) the spatio-temporal patterns of fisheries discards and its underlying drivers in order to identify adequate mitigation strategies; and 2) how we can incorporate discards data in fisheries management plans and conservation strategies. The latest is currently extremely relevant to provide a baseline to new management plans if the European Commission goes ahead with the planned ban on discards in European waters.
Identifying the ecological determinants of bacterial virulence, applying social evolution theory to fisheries management, drivers of ecological stability, intensification of the hydrological cycle, water level fluctuations in lakes due to global climatic drivers and diversity dynamics in the fossil record.