Sexual behavior, heterosexual transmission, and the spread of HIV in sub-Saharan Africa: a simulation study.

A stochastic simulation model has been used to assess the extent to which variation in sexual behavior and transmission characteristics can explain the striking spatial heterogeneity in the prevalence of HIV among different geographical locations in sub-Saharan Africa. Of the various parameters describing sexual behavior the most important determinant of the spread of HIV is the proportion of men engaging in sexual relationships with people other than spouses, including contacts with sex workers and short-term partners. Considering factors other than sexual behavior the model shows that this heterogeneity in HIV prevalence could be the result of differences in the transmission probability of HIV or in the prevalence of other sexuality transmitted diseases. These factors could play a key role in determining the patterns of spread of HIV in sub-Saharan Africa and should be considered in the design of intervention strategies.

[Organization and quality control of a clinical database on intensive care medicine in central and suburban Paris]. / Mise en oeuvre et évaluation d'une base de données commune aux services de réanimation d'Ile-de-France.

BACKGROUND: Epidemiology and medical care appraisal of intensive care medicine relies on the homogeneity of information systems. This work is about a collaborative database related to intensive care units in Paris and its suburb. METHODS: A college of intensivists defined a standard dataset about stays, outcomes, severity of illness, diagnoses and work load, which are collected and analysed by a data management center. A quality control of the database was performed on a random sample of 199 stays. RESULTS: In 1996, 25 intensive care units participated in the database which encompassed more than 35,000 stays. The control of data quality showed a good reliability of data about stays, severity and workload but reproducibility of diagnosis coding has to be improved by means of more accurate coding guidelines. CONCLUSION: This database of case-mix and outcome information allows comparison and medical care appraisal of intensive care units.

Estimation of direct cost and resource allocation in intensive care: correlation with Omega system.

OBJECTIVE: An instrument able to estimate the direct costs of stays in Intensive Care Units (ICUs) simply would be very useful for resource allocation inside a hospital, through a global budget system. The aim of this study was to propose such a tool. DESIGN: Since 1991, a region-wide common data base has collected standard data of intensive care such as the Omega Score, Simplified Acute Physiologic Score, length of stay, length of ventilation, main diagnosis and procedures. The Omega Score, developed in France in 1986 and proved to be related to the workload, was recorded on each patient of the study. SETTING: Eighteen ICUs of Assistance Publique-Hôpitaux de Paris (AP-HP) and suburbs. PATIENTS: 1) Hundred twenty-one randomly selected ICU patients; 2) 12,000 consecutive ICU stays collected in the common data base in 1993. MEASUREMENTS: 1) On the sample of 121 patients, medical expenditure and nursing time associated with interventions were measured through a prospective study. The correlation between Omega points and direct costs was calculated, and regression equations were applied to the 12,000 stays of the data base, leading to estimated costs. 2) From the analytic accounting of AP-HP, the mean direct cost per stay and per unit was calculated, and compared with the mean associated Omega score from the data base. In both methods a comparison of actual and estimated costs was made. RESULTS: The Omega Score is strongly correlated to total direct costs, medical direct costs and nursing requirements. This correlation is observed both in the random sample of 121 stays and on the data base' stays. The discrepancy of estimated costs through Omega Score and actual costs may result from drugs, blood product underestimation and therapeutic procedures not involved in the Omega Score. CONCLUSIONS: The Omega system appears to be a simple and relevant indicator with which to estimate the direct costs of each stay, and then to organise nursing requirements and resource allocation.