Renaud Piarroux

Choice of therapy for imported cases of falciparum malaria in children: a retrospective study of 100 cases seen in Marseilles, France

We have carried out a retrospective study on 100 children in hospital in Marseilles, France with a diagnosis of Plasmodium falciparum malaria. On admission, the main clinical features were anaemia (90 cases), fever (83 cases, > 40 degrees C in 22 cases), hepatomegaly (44 cases), vomiting (29 cases), neurological signs (22 cases), thrombocytopenia (13 cases), hyperparasitaemia (6 cases), jaundice (4 cases), shock (1 case) and hypoglycaemia (1 case). Severe malaria, as defined by the World Health Organization Malaria Action Programme, was rare in our study (only 2 cases) and the prognosis was good (no death, no sequela). The search for neurological signs such as impaired consciousness, prostration or convulsions is an effective and simple way to diagnose potentially severe cases. In the presence of these signs, intravenous quinine treatment resulted in a shortened duration of fever (30 h instead of 63 h) and thereby avoided patients becoming worse. In children without neurological signs or persistent vomiting, oral therapy may be used even if there is high fever or hyperparasitaemia, but close surveillance is required. Patients treated with halofantrine or mefloquine had a shorter stay in hospital than those treated with chloroquine (mean = 4 d instead of 5.7 d). The resistance of some strains to chloroquine may explain this difference.

Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model

BackgroundMathematical models of human mobility have demonstrated a great potential for infectious disease epidemiology in contexts of data scarcity. While the commonly used gravity model involves parameter tuning and is thus difficult to implement without reference data, the more recent radiation model based on population densities is parameter-free, but biased. In this study we introduce the new impedance model, by analogy with electricity. Previous research has compared models on the basis of a few specific available spatial patterns. In this study, we use a systematic simulation-based approach to assess the performances.MethodsFive hundred spatial patterns were generated using various area sizes and location coordinates. Model performances were evaluated based on these patterns. For simulated data, comparison measures were average root mean square error (aRMSE) and bias criteria. Modeling of the 2010 Haiti cholera epidemic with a basic susceptible–infected–recovered (SIR) framework allowed an empirical evaluation through assessing the goodness-of-fit of the observed epidemic curve.ResultsThe new, parameter-free impedance model outperformed previous models on simulated data according to average aRMSE and bias criteria. The impedance model achieved better performances with heterogeneous population densities and small destination populations. As a proof of concept, the basic compartmental SIR framework was used to confirm the results obtained with the impedance model in predicting the spread of cholera in Haiti in 2010.ConclusionsThe proposed new impedance model provides accurate estimations of human mobility, especially when the population distribution is highly heterogeneous. This model can therefore help to achieve more accurate predictions of disease spread in the context of an epidemic.

Targeting hotspots to reduce transmission of malaria in Senegal: modeling of the effects of human mobility

Background In central Senegal malaria incidences have declined in recent years in response to scaling-up of control measures, but now remains stable, making elimination improbable. Additional control measures are needed to reduce transmission. Methods By using a meta-population mathematical model, we evaluated chemotherapy interventions targeting stable malaria hotspots, using a differential equation framework and incorporating human mobility, and fitted to weekly malaria incidences from 45 villages, over 5 years. Three simulated approaches for selecting intervention targets were compared: a) villages with at least one malaria case during the low transmission season of the previous year; b) villages ranked highest in terms of incidence during the high transmission season of the previous year; c) villages ranked based on the degree of connectivity with adjacent populations. Results Our mathematical modeling, taking into account human mobility, showed that the intervention strategies targeting hotspots should be effective in reducing malaria incidence in both treated and untreated areas. Conclusions Mathematical simulations showed that targeted interventions allow increasing malaria elimination potential.