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Understanding the cryptic nature of Lassa fever in West Africa.

ABSTRACT: Lassa fever (LF) is increasingly recognized by global health institutions as an important rodent-borne disease with severe impacts on some of West Africa's poorest communities. However, our knowledge of LF ecology, epidemiology and distribution is limited, which presents barriers to both short-term disease forecasting and prediction of long-term impacts of environmental change on Lassa virus (LASV) zoonotic transmission dynamics. Here, we synthesize current knowledge to show that extrapolations from past research have produced an incomplete picture of the incidence and distribution of LF, with negative consequences for policy planning, medical treatment and management interventions. Although the recent increase in LF case reports is likely due to improved surveillance, recent studies suggest that future socio-ecological changes in West Africa may drive increases in LF burden. Future research should focus on the geographical distribution and disease burden of LF, in order to improve its integration into public policy and disease control strategies.

SUBMITTER: Gibb R

PROVIDER: S-EPMC5694855 | biostudies-other | 2017 Sep

REPOSITORIES: biostudies-other

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Understanding the cryptic nature of Lassa fever in West Africa.

Gibb Rory R Moses Lina M LM Redding David W DW Jones Kate E KE

Pathogens and global health 20170906 6

Lassa fever (LF) is increasingly recognized by global health institutions as an important rodent-borne disease with severe impacts on some of West Africa's poorest communities. However, our knowledge of LF ecology, epidemiology and distribution is limited, which presents barriers to both short-term disease forecasting and prediction of long-term impacts of environmental change on Lassa virus (LASV) zoonotic transmission dynamics. Here, we synthesize current knowledge to show that extrapolations ...[more]

PMID: 28875769

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Project description:BackgroundLassa fever is caused by a viral haemorrhagic arenavirus that affects two to three million people in West Africa, causing a mortality of between 5,000 and 10,000 each year. The natural reservoir of Lassa virus is the multi-mammate rat Mastomys natalensis, which lives in houses and surrounding fields. With the aim of gaining more information to control this disease, we here carry out a spatial analysis of Lassa fever data from human cases and infected rodent hosts covering the period 1965-2007. Information on contemporary environmental conditions (temperature, rainfall, vegetation) was derived from NASA Terra MODIS satellite sensor data and other sources and for elevation from the GTOPO30 surface for the region from Senegal to the Congo. All multi-temporal data were analysed using temporal Fourier techniques to generate images of means, amplitudes and phases which were used as the predictor variables in the models. In addition, meteorological rainfall data collected between 1951 and 1989 were used to generate a synoptic rainfall surface for the same region.Methodology/principal findingsThree different analyses (models) are presented, one superimposing Lassa fever outbreaks on the mean rainfall surface (Model 1) and the other two using non-linear discriminant analytical techniques. Model 2 selected variables in a step-wise inclusive fashion, and Model 3 used an information-theoretic approach in which many different random combinations of 10 variables were fitted to the Lassa fever data. Three combinations of absenceratiopresence clusters were used in each of Models 2 and 3, the 2 absenceratio1 presence cluster combination giving what appeared to be the best result. Model 1 showed that the recorded outbreaks of Lassa fever in human populations occurred in zones receiving between 1,500 and 3,000 mm rainfall annually. Rainfall, and to a much lesser extent temperature variables, were most strongly selected in both Models 2 and 3, and neither vegetation nor altitude seemed particularly important. Both Models 2 and 3 produced mean kappa values in excess of 0.91 (Model 2) or 0.86 (Model 3), making them 'Excellent'.Conclusion/significanceThe Lassa fever areas predicted by the models cover approximately 80% of each of Sierra Leone and Liberia, 50% of Guinea, 40% of Nigeria, 30% of each of Côte d'Ivoire, Togo and Benin, and 10% of Ghana.

Dataset Information

Understanding the cryptic nature of Lassa fever in West Africa.

Publications

Understanding the cryptic nature of Lassa fever in West Africa.

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