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V Isham

Publications and source records attributed to V Isham.

5 recordsLinked to original sources

Surveillance of antimicrobial resistance--what, how and whither?

OBJECTIVE: To express the views of a working party held to consider antibiotic resistance surveillance systems, their strengths and weaknesses, and their current and future applications. METHODS: The participants, all of whom were experienced in this field, discussed the development of surveillance systems in relation to the increasing prevalence of resistance to antibacterial agents and the current interest in surveillance systems shown by many official bodies, in both the human and veterinary fields. The problems inherent in surveillance systems were considered together with the applications of different systems. RESULTS: The properties of good antibiotic resistance surveillance systems were defined. Surveillance systems vary widely from those with a narrow base, focusing on few organisms in one disease area, to those covering many diseases, many organisms (including normal flora) and many compounds. Whatever their design, they should be able to detect significant differences and shifts in susceptibility to various antibacterial agents, and the information derived from them should reach as many interested parties as possible in a timely manner. In using this information to decide strategies, criteria for action need to be determined by pragmatic consensus. Funding remains a major problem, with few large studies being supported by official bodies in spite of their professed enthusiasm for surveillance. In consequence, many current systems are funded by the pharmaceutical industry and are of necessity restricted in their focus. CONCLUSIONS: Antibiotic resistance surveillance studies should and can be well planned and well executed. Many current systems suffer from well-recognized but uncorrected biases. Consortium funding will be necessary for large schemes to be successful. There is no "ideal" surveillance system.

Animals↗

Stochastic host-parasite interaction models.

We contribute to the discussion of causes and effects of aggregation (overdispersion) of macroparasite counts, focussing particularly upon the effects of clumped infections and parasite-induced host mortality. The simple nonlinear stochastic model for the evolution of the parasite load of a single host, investigated in Isham (1995), is extended to allow three parasite stages (larval, mature and offspring), and to allow durations of these stages to be non-exponentially distributed. As in the earlier work, exact algebraic results are possible, providing insight into the aggregation mechanisms, as long as the only source of interaction between host and parasites is an excess host mortality linearly related to the parasite load. Results are obtained on the distribution of parasite load and on host survival. In particular, although parasite-induced host mortality is usually thought of as a process that reduces parasite aggregation (Anderson and Gordon 1982), it is shown that, for this model, parasite-induced host mortality cannot cause the index of dispersion to fall below unity. Host heterogeneity and disease control are also discussed. An approximation based on moment assumptions appropriate to a specially-constructed multivariate negative binomial distribution is proposed. This approximation, which is applicable to other processes, and an alternative based on the multivariate normal distribution are compared with exact results.

Animals↗

Anthelmintic resistance revisited: under-dosing, chemoprophylactic strategies, and mating probabilities.

Deterministic and stochastic models are used to examine the evolution of anthelmintic resistance among trichostrongylid parasites of domestic ruminants. We find that the relative selection pressures exerted by chemoprophylactic (preventive) control strategies, chemotherapeutic (salvage) control strategies, and regimens involving "under-dosing" are critically dependent on a variety of host and parasite parameters (particularly host immunity and grazing behaviour, parasite fecundity, and the survival of the free-living stages on the pasture). Chemoprophylactic strategies are not necessarily more likely to exert a stronger selection pressure than chemotherapeutic strategies. Similarly, as one reduces dosage levels, there is a range of dose levels where under-dosing promotes resistance and a range of dose levels where under-dosing impedes resistance. The most dangerous dose is either that necessary to kill all the susceptible homozygotes, or that necessary to kill all the susceptible homozygotes and all the heterozygotes. Which one prevails depends upon model parameters. The stochastic formulation indicates that spatial heterogeneity in transmission may be a significant force in promoting the spread of resistant genotypes--at least when infection is at low levels.

Animals↗

Assessing the variability of stochastic epidemics.

In predicting the course of individual realizations of an epidemic it is important to know the magnitude of the variability of such realizations about their mean. In this paper and in the context of the general stochastic epidemic, some methods of obtaining approximate estimates of this variability are investigated; one is a multivariate normal approximation based on an asymptotic Gaussian diffusion process, and another uses an approximating linear stochastic process. The extension of these methods to the more detailed models used to describe the transmission dynamics of HIV infection and AIDS is discussed.

Disease Outbreaks↗

Estimation of the incidence of HIV infection.

The aim of the method of 'back projection' is to provide estimates of the number of new infections with the human immunodeficiency virus (HIV) as a function of time, by using the numbers of diagnoses of the acquired immune deficiency syndrome (AIDS) together with information on the distribution of the incubation period between infection and diagnosis. Here, the method is investigated with particular reference to cases of HIV infection and AIDS in the United Kingdom.

Acquired Immunodeficiency Syndrome↗