Sleeping Sickness in Southeastern Uganda: A Spatio-Temporal Analysis of Disease Risk, 1970–2003

Cattle movements and trypanosomes: restocking efforts and the spread of Trypanosoma brucei rhodesiense sleeping sickness in post-conflict Uganda

Background

The northwards spread of acute T. b. rhodesiense sleeping sickness in Uganda has been linked to cattle movements associated with restocking following the end to military conflict in 2006. This study examined the number of cattle traded from T. b. rhodesiense endemic districts, the prevalence of the parasite in cattle being traded and the level of trypanocidal treatment at livestock markets.

Methods

Between 2008 and 2009 interviews were carried out with government veterinarians from 20 districts in Uganda, 18 restocking organisations and numerous livestock traders and veterinarians. Direct observations, a review of movement permit records (2006 to 2008) and blood sampling of cattle (n = 1758) for detection of parasites were also conducted at 10 livestock markets in T. b. rhodesiense endemic districts.

Results

Records available from 8 out of 47 identified markets showed that 39.5% (5,238/13,267) of the inter-district cattle trade between mid-2006 and mid-2008 involved movement from endemic areas to pathogen-free districts. PCR analysis showed a prevalence of 17.5% T. brucei s.l. (n = 307/1758 [95% CI: 15.7-19.2]) and 1.5% T. b. rhodesiense (n = 26/1758 [95% CI: 0.9-2.0]) from these same markets. In a two-year period, between late-2006 to late-2008, an estimated 72,321 to 86,785 cattle (57, 857 by 18 restocking organisations and 10,214 to 24,679 by private traders) were imported into seven pathogen-free northern districts, including districts that were endemic for T. b. gambiense. Between 281 and 1,302 of these cattle were likely to have carried T. b. rhodesiense. While governmental organisations predominantly adhered to trypanocidal treatment, most Non-Governmental Organisations (NGOs) and private traders did not. Inadequate market infrastructure, poor awareness, the need for payment for drug treatments, and the difficulty in enforcing a policy of treatment at point of sale contributed to non-compliance.

Conclusion

With increasing private trade, preventing the spread of Rhodesian sleeping sickness in Uganda requires government support to ensure mandatory trypanocidal treatment at livestock markets, investment in market infrastructure and possible drug subsidy. Mapping the northern reaches of T. b. rhodesiense in livestock and preparation of risk assessments for cattle trading could mitigate future outbreaks.

Remote sensing of climatic anomalies and West Nile virus incidence in the northern Great Plains of the United States

The northern Great Plains (NGP) of the United States has been a hotspot of West Nile virus (WNV) incidence since 2002. Mosquito ecology and the transmission of vector-borne disease are influenced by multiple environmental factors, and climatic variability is an important driver of inter-annual variation in WNV transmission risk. This study applied multiple environmental predictors including land surface temperature (LST), the normalized difference vegetation index (NDVI) and actual evapotranspiration (ETa) derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) products to establish prediction models for WNV risk in the NGP. These environmental metrics are sensitive to seasonal and inter-annual fluctuations in temperature and precipitation, and are hypothesized to influence mosquito population dynamics and WNV transmission. Non-linear generalized additive models (GAMs) were used to evaluate the influences of deviations of cumulative LST, NDVI, and ETa on inter-annual variations of WNV incidence from 2004–2010. The models were sensitive to the timing of spring green up (measured with NDVI), temperature variability in early spring and summer (measured with LST), and moisture availability from late spring through early summer (measured with ETa), highlighting seasonal changes in the influences of climatic fluctuations on WNV transmission. Predictions based on these variables indicated a low WNV risk across the NGP in 2011, which is concordant with the low case reports in this year. Environmental monitoring using remote-sensed data can contribute to surveillance of WNV risk and prediction of future WNV outbreaks in space and time.

Agricultural, socioeconomic and environmental variables as risks for human verotoxigenic Escherichia coli (VTEC) infection in Finland

Background

Verotoxigenic E. coli (VTEC) is the cause of severe gastrointestinal infection especially among infants. Between 10 and 20 cases are reported annually to the National Infectious Disease Register (NIDR) in Finland. The aim of this study was to identify explanatory variables for VTEC infections reported to the NIDR in Finland between 1997 and 2006. We applied a hurdle model, applicable for a dataset with an excess of zeros.

Methods

We enrolled 131 domestically acquired primary cases of VTEC between 1997 and 2006 from routine surveillance data. The isolated strains were characterized by virulence type, serogroup, phage type and pulsed-field gel electrophoresis. By applying a two-part Bayesian hurdle model to infectious disease surveillance data, we were able to create a model in which the covariates were associated with the probability for occurrence of the cases in the logistic regression part and the magnitude of covariate changes in the Poisson regression part if cases do occur. The model also included spatial correlations between neighbouring municipalities.

Results

The average annual incidence rate was 4.8 cases per million inhabitants based on the cases as reported to the NIDR. Of the 131 cases, 74 VTEC O157 and 58 non-O157 strains were isolated (one person had dual infections). The number of bulls per human population and the proportion of the population with a higher education were associated with an increased occurrence and incidence of human VTEC infections in 70 (17%) of 416 of Finnish municipalities. In addition, the proportion of fresh water per area, the proportion of cultivated land per area and the proportion of low income households with children were associated with increased incidence of VTEC infections.

Conclusions

With hurdle models we were able to distinguish between risk factors for the occurrence of the disease and the incidence of the disease for data characterised by an excess of zeros. The density of bulls and the proportion of the population with higher education were significant both for occurrence and incidence, while the proportion of fresh water, cultivated land, and the proportion of low income households with children were significant for the incidence of the disease.

Spatio-temporal modeling of sparse geostatistical malaria sporozoite rate data using a zero inflated binomial model

The proportion of malaria vectors harboring the infectious stage of the parasite (the sporozoite rates) is an important component of measures of malaria transmission. Variation in time and/or space in sporozoite rates contribute substantially to spatio-temporal variation in transmission. However, because most vectors test negative for sporozoites, sporozoite rate data are sparse with large number of observed zeros across locations or over time in the case of longitudinal data. Rarely are appropriate methods and models used in analyzing such data. In this study, Bayesian zero inflated binomial (ZIB) geostatistical models were developed and compared with standard binomial analogues to analyze sporozoite data obtained from the KEMRI/CDC health and demographic surveillance system (HDSS) site in rural Western Kenya during 2002-2004. ZIB models showed a better predictive ability, identified more significant covariates and obtained narrower credible intervals for all parameters compared to standard geostatistical binomial model.