Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

Abstract Background The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Conclusion Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Non-linear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation.</p

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

12 p.International audienceBackground: The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods: A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results: The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemoepidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Conclusion: Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Nonlinear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation

Characteristics of HIV-2 and HIV-1/HIV-2 Dually Seropositive Adults in West Africa Presenting for Care and Antiretroviral Therapy: The IeDEA-West Africa HIV-2 Cohort Study.

HIV-2 is endemic in West Africa. There is a lack of evidence-based guidelines on the diagnosis, management and antiretroviral therapy (ART) for HIV-2 or HIV-1/HIV-2 dual infections. Because of these issues, we designed a West African collaborative cohort for HIV-2 infection within the framework of the International epidemiological Databases to Evaluate AIDS (IeDEA).We collected data on all HIV-2 and HIV-1/HIV-2 dually seropositive patients (both ARV-naive and starting ART) and followed-up in clinical centres in the IeDEA-WA network including a total of 13 clinics in five countries: Benin, Burkina-Faso Côte d'Ivoire, Mali, and Senegal, in the West Africa region.Data was merged for 1,754 patients (56% female), including 1,021 HIV-2 infected patients (551 on ART) and 733 dually seropositive for both HIV-1 and HIV 2 (463 on ART). At ART initiation, the median age of HIV-2 patients was 45.3 years, IQR: (38.3-51.7) and 42.4 years, IQR (37.0-47.3) for dually seropositive patients (p = 0.048). Overall, 16.7% of HIV-2 patients on ART had an advanced clinical stage (WHO IV or CDC-C). The median CD4 count at the ART initiation is 166 cells/mm(3), IQR (83-247) among HIV-2 infected patients and 146 cells/mm(3), IQR (55-249) among dually seropositive patients. Overall, in ART-treated patients, the CD4 count increased 126 cells/mm(3) after 24 months on ART for HIV-2 patients and 169 cells/mm(3) for dually seropositive patients. Of 551 HIV-2 patients on ART, 5.8% died and 10.2% were lost to follow-up during the median time on ART of 2.4 years, IQR (0.7-4.3).This large multi-country study of HIV-2 and HIV-1/HIV-2 dual infection in West Africa suggests that routine clinical care is less than optimal and that management and treatment of HIV-2 could be further informed by ongoing studies and randomized clinical trials in this population