David Kault

Hendra virus survival does not explain spillover patterns and implicates relatively direct transmission routes from flying foxes to horses.

Hendra virus (HeV) is lethal to humans and horses, and little is known about its epidemiology. Biosecurity restrictions impede advances, particularly on understanding pathways of transmission. Quantifying the environmental survival of HeV can be used for making decisions and to infer transmission pathways. We estimated HeV survival with a Weibull distribution and calculated parameters from data generated in laboratory experiments. HeV survival rates based on air temperatures 24 h after excretion ranged from 2 to 10 % in summer and from 12 to 33 % in winter. Simulated survival across the distribution of the black flying fox (Pteropus alecto), a key reservoir host, did not predict spillover events. Based on our analyses we concluded that the most likely pathways of transmission did not require long periods of virus survival and were likely to involve relatively direct contact with flying fox excreta shortly after excretion.

Modelling the effects of AIDS on gonorrhea epidemiology

A dramatic decline in gonorrhea has been observed in some American homosexual communities since the advent of AIDS. It has been suggested that this decline is a good indicator of voluntary behavioural change in response to the threat of AIDS. A model is developed here to assess the effects of gonorrhea epidemiology of removals from the community as a result of AIDS. The model allows for a continuous distribution of sexual partner exchange rate and a variable degree of correlation between the rates of those involved in a partnership. Output of the model using plausible parameter values shows that it is possible to explain most or all of the decline in gonorrhea by sickness and deaths due to HIV/AIDS. Therefore, the decline in gonorrhea should not be automatically accepted as evidence of appropriate behavioural change.

Assessing the National HIV/AIDS Strategy Evaluation

The report is a useful compilation of data on Australias HIV/AIDS epidemic and the response to it. The report produces firm evidence for endorsing Australias success in limiting the spread of HIV by a number of routes. Australia has been successful in preventing iatrogenic spread, spread through commercial sex and spread through injecting drug use. In the latter case however, the hepatitis C epidemic cautions against complacency. The report, unfortunately, does not recognise very serious weaknesses in the evidence it uses as a basis for its endorsement of current efforts against HIV in the male homosexual community and the general heterosexual community. The report recognises failure of current policies in Aboriginal and Torres Strait Islander communities and recognises the threat posed here by HIV but recommends no major policy change. There is some recognition of the limitation of the data, but no recommendation for increased surveillance. The report ignores methods of prevention other than public health education.

Modeling AIDS as a function of other sexually transmitted disease

The spread of AIDS, as with any sexually transmitted disease, will depend on the pattern of sexual activity. Both the proportion of the population who have high partner exchange rates and the extent to which that proportion interacts with the remainder of the population are likely to be important determinants of the AIDS epidemic. However, it does not seem likely that surveys could obtain sufficiently reliable information of this nature for use in an accurate model of the AIDS epidemic. On the other hand, such information is implicitly contained in the epidemiology of other sexually transmitted diseases (STDs). Therefore a method is suggested of calculating the parameters of a model of the AIDS epidemic by comparing it with the epidemiology of another STD. The result is a model that predicts the likelihood of infection by the AIDS virus as a function of time and an individuals history of STD. It is suggested that further work along these lines may lead to a quantitative approach to assessing the importance of various STDs as cofactors in the spread of AIDS.

False negatives in evidence based medicine

Evidence Based Medicine (EBM) is a term used for the current dominant methodology for deciding what medical treatments should be accepted as valid. It places great emphasis on Randomised Clinical Trials (RCTs) which are analysed according to a strict frequentist paradigm, with a rigid p-value ≤0.05 criterion but with little consideration of prior probabilities or the cost of errors. Accordingly, low cost, safe treatments where there is prior knowledge of at least slight effectiveness, may often be inappropriately discarded by EBM. The Cochrane Collaboration is an online central repository of RCTs and meta-analyses of RCTs. This paper uses statistical methods applied to a random sample of outcomes listed in the Cochrane Collaboration, to estimate the negative predictive value when treatments are declared ineffective as a result of positive outcomes which do not achieve the p≤ 0.05 criterion. The data were analysed using six different models in order to determine the proportion of genuinely ineffective treatments in the set of all positive outcomes where p>0.05. All six methods give point estimates substantially less than half for the negative predictive value when the decision rule is to declare treatments to be ineffective when their outcome is positive but p>0.05. Although confidence interval estimation indicates considerable uncertainty in these estimates, it seems reasonable to conclude that when a RCT gives a positive outcome but p0.05, the conventional EBM decision to declare the treatment to be ineffective, is likely to be wrong more often than not.

Assessment of sexual mixing patterns.

The manner in which people with varying partner change rates choose their partners may have important implications for the future of the AIDS epidemic. A relatively rapid but small epidemic can be expected if sexual mixing patterns are highly assortative so that those with high partner change rates nearly always choose partners with similar rates. Direct estimation of sexual mixing is exceedingly difficult. On the other hand, information on the way people mix is implicitly contained in the epidemiology of other sexually transmitted diseases (STDs). If mixing is highly assortative, one might expect gonorrhea to be largely confined to a small subsection of the population who would frequently contract the disease repeatedly. In this paper a model of gonorrhea transmission in which partner change rates and preference are dealt with as continuous variables is used to extract information on mixing from data on an Australian heterosexual population. It was found that in this population mixing is not far from random with respect to partner change rates.

Emergency department presentations during the State of Origin rugby league series: a retrospective statewide analysis

Objective: To evaluate the effect of the State of Origin rugby league series on the number of emergency department (ED) presentations in Queensland.

From P-Values to Objective Probabilities in Assessing Medical Treatments.

The assessment of the effectiveness of a treatment in a clinical trial, depends on calculating p-values. However, p-values are only indirect and partial indicators of a genuine effect. Particularly in situations where publication bias is very likely, assessment using a p-value of 0.05 may not be sufficiently cautious. In other situations it seems reasonable to believe that assessment based on p-values may be unduly conservative. Assessments could be improved by using prior information. This implies using a Bayesian approach to take account of prior probability. However, the use of prior information in the form of expert opinion can allow bias. A method is given here that applies to assessments already included or likely to be included in the Cochrane Collaboration, excluding those reviews concerning new drugs. This method uses prior information and a Bayesian approach, but the prior information comes not from expert opinion but simply from the distribution of effectiveness apparent in a random sample of summary statistics in the Cochrane Collaboration. The method takes certain types of summary statistics and their confidence intervals and with the help of a graph, translates this into probabilities that the treatments being trialled are effective.

Impact of a structured intern education programme on clinical documentation in the emergency department

To evaluate the impact of More Learning for Interns in Emergency (MoLIE) on clinical documentation in the ED of a large regional hospital.

The Maimed Martian, credible intervals and bias against benefit

A sad little story about a maimed Martian astronaut is used to illustrate a method of improving confidence interval (CI) calculations. CIs in medical statistics are currently calculated from the data available in a clinical trial or meta-analysis considered in isolation from all other information available on earth. Likewise, the Martian in the story uses only information available to it, in isolation from further information from earth. However, there is further objective knowledge available to people on earth to improve the Martians estimate. In the same way, we have objective prior knowledge available to us outside of the current clinical trial results which we can use to improve CI calculations. This prior knowledge is incorporated into the CI calculations using Bayesian methods. The objective prior knowledge that is available is the fact that there were researchers who felt it worthwhile to conduct the trial and journal editors who felt it worthwhile publishing the results. It is shown here that the use of this information contracts the width of the log CI by a factor of about three quarters on average. Unlike standard CIs, these new intervals also have the advantage of being directly interpretable in terms of probabilities. These probabilities also enable calculation of improved point estimates. These calculations are applied to 100 randomly selected Cochrane systematic reviews and show serious problems in assessing medical treatments. For treatments not involving new drugs or devices, it is shown that there is evidence of a bias towards a negative assessment. The calculations here make a quantitative adjustment for publication bias. They show that the proportion of negative assessments do not reflect an appropriate adjustment for publication bias.