Climate Predictors of the Spatial Distribution of Human Plague Cases in the West Nile Region of Uganda

MacMillan, Katherine; Monaghan, Andrew J.; Apangu, Titus; Griffith, Kevin S.; Mead, Paul S.; Acayo, Sarah; Acidri, Rogers; Moore, Sean M.; Mpanga, Joseph T.; Enscore, Russell E.; Gage, Kenneth L.; Eisen, Rebecca J.

doi:10.4269/ajtmh.2012.11-0569

Cited by 23 publications

(27 citation statements)

References 53 publications

(95 reference statements)

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“…For example Neerinckx et al (2008Neerinckx et al ( , 2010 reported a positive correlation of high plague frequency at an elevation above 1,500m in West Usambara Mountains. Similar results have been reported by MacMillan et al (2012) who indicated a high correlation between plague hosts and elevation above 1,300m in a plague focus in Uganda. Also, elevation has been reported to influence plague host occurrence in Turkey (Yigit et al, 2003).…”

Section: Discussionsupporting

confidence: 90%

Landform and surface attributes for prediction of rodent burrows in the Western Usambara Mountains, Tanzania

Meliyo

Massawe

Msanya

et al. 2014

Tanzania J Hlth Res

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Previous studies suggest that rodent burrows, a proxy for rodent population are important for predicting plague risk areas. However, studies that link landform, surface attributes and rodent burrows in the Western Usambara Mountains in Tanzania are scanty. Therefore, this study was conducted in plague endemic area of the Western Usambara Mountains in northern, Tanzania, to explore the relationship between rodent burrows, and landform and surface attributes. The study was carried out in three areas corresponding to high (Lokome), medium (Lukozi) and low (Mwangoi) frequency of reported plague cases. Data were collected from 117, 200 and 170 observation sites for Lokome, Lukozi and Mwangoi, respectively using 100 m x 200 m quadrats. Remote sensing and field surveys were used to collect data on landform and surface attributes. Rodent burrows were surveyed and quantified by counting the number of burrows in 20m x 20m grids demarcated on the main 100m x 200m quadrats. The collected data were analysed in R software using boosted regression trees (BRT) technique. Rodent burrows were found at an elevation of above 1600m in the high and medium plague frequency landscapes. No burrows were found in the low plague frequency landscape situated below 1500m. BRT analysis shows a significant relationship between landform characteristics and rodent burrows in both high and medium plague frequency landscapes. Overall, elevation and hillshade are the most important determinants of rodent burrow distribution in the studied landscapes. It is concluded that in high altitudes, specific landform attributes (hill-shade, slope, elevation) and vegetation cover-favour rodent burrowing.

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Section: Discussionsupporting

confidence: 90%

Landform and surface attributes for prediction of rodent burrows in the Western Usambara Mountains, Tanzania

Meliyo

Massawe

Msanya

et al. 2014

Tanzania J Hlth Res

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“…Furthermore, covariates included in these models suggested that localities that are generally wetter, but with discontinuous rainfall, pose an increased risk for plague compared with drier areas. 11,12,14 Although existing spatial models performed well in broadly defining the plague focus, there were many villages within the focus where human plague cases had not been reported by clinics during approximately a decade of surveillance. Such an observation raised the question of whether these disparities in case counts among villages within the risk area were attributable to differences in access to care, care-seeking behavior or knowledge of plague, agricultural or food storage practices, rodent and vector control strategies, or fine-scale ecologic differences (e.g., differences in host and flea community structure).…”

Section: Introductionmentioning

confidence: 99%

“…10 To aid in better targeting plague prevention resources, recent research efforts in Uganda have sought to define when and where humans are most at risk for plague in the far eastern edge of this plague focus. [11][12][13][14] During August 1999-July 2011, a total of 2,409 suspect plague cases were reported from the West Nile Region of Uganda; most cases occurred during September-December, a time period that corresponds with the primary rainy season. 13 Modeling of inter-annual variation showed that annual plague case counts were negatively associated with dry season rainfall (December-February) and positively associated with rainfall immediately preceding the plague season.…”

Section: Introductionmentioning

confidence: 99%

Identification of Risk Factors for Plague in the West Nile Region of Uganda

Eisen

MacMillan

Atiku

et al. 2014

The American Society of Tropical Medicine and Hygiene

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Abstract. Plague is an often fatal, primarily flea-borne rodent-associated zoonosis caused by Yersinia pestis. We sought to identify risk factors for plague by comparing villages with and without a history of human plague cases within a model-defined plague focus in the West Nile Region of Uganda. Although rat (Rattus rattus) abundance was similar inside huts within case and control villages, contact rates between rats and humans (as measured by reported rat bites) and host-seeking flea loads were higher in case villages. In addition, compared with persons in control villages, persons in case villages more often reported sleeping on reed or straw mats, storing food in huts where persons sleep, owning dogs and allowing them into huts where persons sleep, storing garbage inside or near huts, and cooking in huts where persons sleep. Compared with persons in case villages, persons in control villages more commonly reported replacing thatch roofing, and growing coffee, tomatoes, onions, and melons in agricultural plots adjacent to their homesteads. Rodent and flea control practices, knowledge of plague, distance to clinics, and most care-seeking practices were similar between persons in case villages and persons in control villages. Our findings reinforce existing plague prevention recommendations and point to potentially advantageous local interventions.

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“…However, in other tropical and sub-tropical regions plague generally occurs during the rainy season or shows no clear seasonal pattern [44], [45]. In addition, previous research in the West Nile region of Uganda established a positive link between rainfall in February, October, and November (but a negative association with June rainfall) and the spatial risk of plague [40].…”

Section: Discussionmentioning

confidence: 99%

Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda

et al. 2012

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Climate and weather influence the occurrence, distribution, and incidence of infectious diseases, particularly those caused by vector-borne or zoonotic pathogens. Thus, models based on meteorological data have helped predict when and where human cases are most likely to occur. Such knowledge aids in targeting limited prevention and control resources and may ultimately reduce the burden of diseases. Paradoxically, localities where such models could yield the greatest benefits, such as tropical regions where morbidity and mortality caused by vector-borne diseases is greatest, often lack high-quality in situ local meteorological data. Satellite- and model-based gridded climate datasets can be used to approximate local meteorological conditions in data-sparse regions, however their accuracy varies. Here we investigate how the selection of a particular dataset can influence the outcomes of disease forecasting models. Our model system focuses on plague (Yersinia pestis infection) in the West Nile region of Uganda. The majority of recent human cases have been reported from East Africa and Madagascar, where meteorological observations are sparse and topography yields complex weather patterns. Using an ensemble of meteorological datasets and model-averaging techniques we find that the number of suspected cases in the West Nile region was negatively associated with dry season rainfall (December-February) and positively with rainfall prior to the plague season. We demonstrate that ensembles of available meteorological datasets can be used to quantify climatic uncertainty and minimize its impacts on infectious disease models. These methods are particularly valuable in regions with sparse observational networks and high morbidity and mortality from vector-borne diseases.

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Climate Predictors of the Spatial Distribution of Human Plague Cases in the West Nile Region of Uganda

Cited by 23 publications

References 53 publications

Landform and surface attributes for prediction of rodent burrows in the Western Usambara Mountains, Tanzania

Landform and surface attributes for prediction of rodent burrows in the Western Usambara Mountains, Tanzania

Identification of Risk Factors for Plague in the West Nile Region of Uganda

Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda

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