PubMed Health⌕ Search

Biomedical subjects

Rowland R Kao

Publications and source records attributed to Rowland R Kao.

12 recordsLinked to original sources
PubMed2025

Sociality and kinship constrain the free-mixing of pathogens in a wild mammal host population.

Pathogens rarely mix freely throughout host populations, and the presence of barriers to transmission can be detected as patterns of increased genetic isolation among pathogen isolates. Despite the importance of transmission patterns in host societies, and the risk of epizootics from wildlife disease systems, barriers to open pathogen transmission are poorly understood in wild hosts. We tested the influence of host kinship and social structure on genetic divergence among strains of Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), in a wild badger population. We measured genetic distances between M. bovis isolates from badger hosts that varied in their own genetic similarity (a proxy for kinship) and in their social group affiliations. Using jack-knifing analyses to control for pseudoreplication, we found that genetic distances between pathogen isolates decreased with increasing kinship of host dyads, but only when hosts shared the same social group. Our findings suggest that the open transmission of bTB in wild hosts is constrained by a combination of social and kin structure, in particular the sharing of similar pathogen strains among kin within social groups. We discuss the implications of these transmission structures for the understanding and management of wildlife diseases.

Animals↗
PubMed2006

The network of sheep movements within Great Britain: Network properties and their implications for infectious disease spread.

During the 2001 foot and mouth disease epidemic in the UK, initial dissemination of the disease to widespread geographical regions was attributed to livestock movement, especially of sheep. In response, recording schemes to provide accurate data describing the movement of large livestock in Great Britain (GB) were introduced. Using these data, we reconstruct directed contact networks within the sheep industry and identify key epidemiological properties of these networks. There is clear seasonality in sheep movements, with a peak of intense activity in August and September and an associated high risk of a large epidemic. The high correlation between the in and out degree of nodes favours disease transmission. However, the contact networks were largely dissasortative: highly connected nodes mostly connect to nodes with few contacts, effectively slowing the spread of disease. This is a result of bipartite-like network properties, with most links occurring between highly active markets and less active farms. When comparing sheep movement networks (SMNs) to randomly generated networks with the same number of nodes and node degrees, despite structural differences (such as disassortativity and higher frequency of even path lengths in the SMNs), the characteristic path lengths within the SMNs are close to values computed from the corresponding random networks, showing that SMNs have 'small-world'-like properties. Using the network properties, we show that targeted biosecurity or surveillance at highly connected nodes would be highly effective in preventing a large and widespread epidemic.

Animal Husbandry↗
PubMed2006

Evolution of pathogens towards low R0 in heterogeneous populations.

Maximization of the basic reproduction ratio or R(0) is widely believed to drive the emergence of novel pathogens. The presence of exploitable heterogeneities in a population, such as high variance in the number of potentially infectious contacts, increases R(0) and thus pathogens that can exploit heterogeneities in the contact structure have an advantage over those that do not. However, exploitation of heterogeneities results in a more rapid depletion of the potentially susceptible neighbourhood for an infected host. Here a simple model of pathogen evolution in a heterogeneous environment is developed and placed in the context of HIV transmission. In this model, it is shown that pathogens may evolve towards lower R(0), even if this results in pathogen extinction. For sufficiently high transmissibility, two locally stable strategies exist for an evolving pathogen, one that exploits heterogeneities and results in higher R(0), and one that does not, and results in lower R(0). While the low R(0) strategy is never evolutionarily stable, invading strains with higher R(0) will also converge to the low R(0) strategy if not sufficiently different from the resident strain. Heterogenous transmission is increasingly recognized as fundamental to epidemiological dynamics and the evolution of pathogens; here, it is shown that the ability to exploit heterogeneity is a strategy that can itself evolve.

Disease Outbreaks↗
PubMed2006

The effect of contact heterogeneity and multiple routes of transmission on final epidemic size.

Heterogeneity in the number of potentially infectious contacts amongst members of a population increases the basic reproduction ratio (R(0)) and markedly alters disease dynamics compared to traditional mean-field models. Most models describing transmission on contact networks only account for one specific route of transmission. However, for many infectious diseases multiple routes of transmission exist. The model presented here captures transmission through a well defined network of contacts, complemented by mean-field type transmission amongst the nodes of the network that accounts for alternative routes of transmission. The impact of these combined transmission mechanisms on the final epidemic size is investigated analytically. The analytic predictions for the purely mean-field case and the transmission through the network-only case are confirmed by individual-based network simulations. There is a critical transmission potential above which an increased contribution of the mean-field type transmission increases the final epidemic size while an increased contribution of the transmission through the network decreases it. Below the critical transmission potential the opposite effect is observed.

Communicable Diseases↗
PubMed2006

Infectious disease control using contact tracing in random and scale-free networks.

Contact tracing aims to identify and isolate individuals that have been in contact with infectious individuals. The efficacy of contact tracing and the hierarchy of traced nodes-nodes with higher degree traced first-is investigated and compared on random and scale-free (SF) networks with the same number of nodes N and average connection K. For values of the transmission rate larger than a threshold, the final epidemic size on SF networks is smaller than that on corresponding random networks. While in random networks new infectious and traced nodes from all classes have similar average degrees, in SF networks the average degree of nodes that are in more advanced stages of the disease is higher at any given time. On SF networks tracing removes possible sources of infection with high average degree. However a higher tracing effort is required to control the epidemic than on corresponding random networks due to the high initial velocity of spread towards the highly connected nodes. An increased latency period fails to significantly improve contact tracing efficacy. Contact tracing has a limited effect if the removal rate of susceptible nodes is relatively high, due to the fast local depletion of susceptible nodes.

Animals↗
PubMed2005

Parameterization of individual-based models: comparisons with deterministic mean-field models.

The relating of deterministic, mean-field models into network models, where epidemic spread occurs between interconnected susceptible and infectious individuals or populations, requires careful consideration. Here, we discuss models that consider differently the manner in which contact rate and infectiousness change over time, with different algorithms suitable for different underlying processes. Though these models give coincidental results to the mean-field in the case of large, highly connected networks, the results when sparsely connected networks are considered may differ. Different subsets of the parameters from the mean-field epidemic (R(0), generation time, infectiousness, etc.) are preserved in each case. Despite these differences, simulated epidemics generated under some model architectures are insensitive to the average degree of contact amongst nodes, k. Model-based estimates of k may be model dependent, and must therefore be viewed with caution.

Algorithms↗
PubMed2005

Disease contact tracing in random and clustered networks.

The efficacy of contact tracing, be it between individuals (e.g. sexually transmitted diseases or severe acute respiratory syndrome) or between groups of individuals (e.g. foot-and-mouth disease; FMD), is difficult to evaluate without precise knowledge of the underlying contact structure; i.e. who is connected to whom? Motivated by the 2001 FMD epidemic in the UK, we determine, using stochastic simulations and deterministic 'moment closure' models of disease transmission on networks of premises (nodes), network and disease properties that are important for contact tracing efficiency. For random networks with a high average number of connections per node, little clustering of connections and short latency periods, contact tracing is typically ineffective. In this case, isolation of infected nodes is the dominant factor in determining disease epidemic size and duration. If the latency period is longer and the average number of connections per node small, or if the network is spatially clustered, then the contact tracing performs better and an overall reduction in the proportion of nodes that are removed during an epidemic is observed.

Communicable Disease Control↗
PubMed2003

The impact of local heterogeneity on alternative control strategies for foot-and-mouth disease.

The 2001 epidemic of foot-and-mouth disease (FMD) in the UK resulted in the death of nearly 10 million livestock at a cost that was estimated to be up to 8 billion pounds. Owing to the controversy surrounding the epidemic, the question of whether or not alternative policies would have resulted in significantly better control of the epidemic remains of great interest. A hexagonal lattice simulation of FMD in Cumbria is used to address the central question of whether or not better use could have been made of expert knowledge of FMD transmission to target pre-emptive culling, by assuming that the premises at greatest risk of becoming infected can be targeted for culling. The 2000 UK census and the epidemiological database collected during the epidemic are used to describe key characteristics of disease transmission, and the model is fit to the epidemic time-series. Under the assumptions of the model, the parameters that best fit the epidemic in Cumbria indicate that a policy based on expert knowledge would have exacerbated the epidemic compared with the policy as implemented. However, targeting more distant, high-risk farms could be more valuable under different epidemic conditions, notably, if risk factors of sufficient magnitude could be identified to aid in prioritizing vaccination or culling of farms at high risk of becoming infected.

Animals↗
PubMed2002

The role of mathematical modelling in the control of the 2001 FMD epidemic in the UK.

Mathematical models played an important role in guiding the development of the control policies in the 2001 foot-and-mouth disease epidemic in the UK. The variety of approaches that helped to guide the policy can sometimes be confusing. Here, the different modelling exercises that were developed over the course of the epidemic are reviewed, describing the difficulties in interpreting the available data and the appropriateness of the various assumptions.

Animals↗
PubMed2002

BSE - a wolf in sheep's clothing?

The entire sheep flock in the UK has been threatened with slaughter if BSE is found in farmed sheep, largely on the grounds that an epidemic of BSE in sheep could be harder to contain than was the case for cattle, and that lamb could present a greater risk to consumers than beef. However, identifying BSE in a sheep is not straightforward, because of its similarities to the related disease, scrapie. Here, we review the likelihood that any UK sheep have BSE, how they might have got it, how a case could be identified and what the Government is doing in terms of surveillance and possible control methods.

Alleles↗