Brandt, Patrick T.
Permanent URI for this collectionhttps://hdl.handle.net/10735.1/5909
Patrick Brandt is a Professor of Political Science and a Faculty Associate at UT Dallas' Center for Global Collective Action. His research interests include:
- Forecasting methodology and evaluation,
- GDELT,
- Inter- and intra-state conflict,
- International and comparative political economy,
- Terrorism, and
- Vector agression: VAR, SVAR BVAR.
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Item Burden of Salmonellosis, Campylobacteriosis and Listeriosis: A Time Series Analysis, Belgium, 2012 to 2020(European Centre for Disease Prevention & Control, 2018-08-20) de Noordhout, C. Maertens; Devleesschauwer, B.; Haagsma, J. A.; Havelaar, A. H.; Bertrand, S.; Vandenberg, O.; Quoilin, S.; Brandt, Patrick T.; Speybroeck, N.; Brandt, Patrick T.Salmonellosis, campylobacteriosis and listeriosis are food-borne diseases. We estimated and forecasted the number of cases of these three diseases in Belgium from 2012 to 2020, and calculated the corresponding number of disability-adjusted life years (DALYs). The salmonellosis time series was fitted with a Bai and Perron two-breakpoint model, while a dynamic linear model was used for campylobacteriosis and a Poisson autoregressive model for listeriosis. The average monthly number of cases of salmonellosis was 264 (standard deviation (SD): 86) in 2012 and predicted to be 212 (SD: 87) in 2020; campylobacteriosis case numbers were 633 (SD: 81) and 1,081 (SD: 311); listeriosis case numbers were 5 (SD: 2) in 2012 and 6 (SD: 3) in 2014. After applying correction factors, the estimated DALYs for salmonellosis were 102 (95% uncertainty interval (UI): 8-376) in 2012 and predicted to be 82 (95% UI: 6-310) in 2020; campylobacteriosis DALYs were 1,019 (95% UI: 137-3,181) and 1,736 (95% UI: 178-5,874); listeriosis DALYs were 208 (95% UI: 192226) in 2012 and 252 (95% UI: 200-307) in 2014. New actions are needed to reduce the risk of food-borne infection with Campylobacter spp. because campylobacteriosis incidence may almost double through 2020.Item Long-Lasting Insecticide Net Ownership, Access and Use in Southwest Ethiopia: A Community-Based Cross-Sectional Study(MDPI AG, 2018-11-05) Seyoum, Dinberu; Speybroeck, Niko; Duchateau, Luc; Brandt, Patrick T.; Rosas-Aguirre, Angel; Brandt, Patrick T.Introduction: A large proportion of the Ethiopian population (approximately 68%) lives in malaria risk areas. Millions of long-lasting insecticide treated nets (LLINs) have been distributed as part of the malaria prevention and control strategy in the country. This study assessed the ownership, access and use of LLNs in the malaria endemic southwest Ethiopia. Methods: A community-based cross-sectional study was conducted in southwest Ethiopia during October-November 2015, including 836 households from sixteen villages around Gilgel-Gibe dam area. Indicators of ownership, access and use of LLINs were derived following the Roll Back Malaria (RBM) guidelines. Factors associated with failure for both LLIN access and use were analysed at household level using a multivariate logistic regression model. Results: The proportion of households with at least one LLIN was 82.7% (95% CI: 80.0, 85.1). However, only 68.9% (95% CI: 65.6, 71.9) had enough LLINs to cover all family members (with ≥ 1 LLIN for every two persons). While 75.3% (95% CI: 68.4, 83.0) of the population was estimated to have accessed to LLINs, only 63.8% (95% CI: 62.3, 65.2) reported to have used a LLIN the previous night. The intra-household gap (i.e., households owning at least one LLIN, but unable to cover all family members) and the behavioral gap (i.e., household members who did not sleep under a LLIN despite having access to one) were 16.8% and 10.5%, respectively. Age, marital status and education of household heads, as well as household size and cooking using firewood were associated with the access to enough LLINs within households. Decreased access to LLINs at households was the main determinant for not achieving ≥ 80% household members sleeping under a LLIN the previous night. Other associated factors were household size and education level of household head. Conclusions: LLIN coverage levels in study villages remain below national targets of 100% for ownership and 80% for use. The access to enough LLINs within the households is the main restriction of LLIN use in the study area.Item Money and Rhetoric: Energy Sector Dynamics in U.S. Senate Committee(Elsevier Inc., 2020-02-12) Iliev, I. R.; Brandt, Patrick T.; Brandt, Patrick T.The sequencing of the relationship between campaign contributions and legislative rhetoric is categorized by competing theories as being driven by lags, leads, and contemporaneous effects. We study the committee level dynamics between energy sector donations and legislative rhetoric in the U.S. Senate. Conditioning on party and Senate class, we find evidence for complex interactions that are characterized by a combination of various temporal responses. Individual dynamics — electoral vulnerability, geographical differences and the state-specific importance of the sector — lead to stronger connections between campaign contributions and rhetoric. ©2019 Western Social Science AssociationItem True Malaria Prevalence in Children under Five: Bayesian Estimation Using Data of Malaria Household Surveys from Three Sub-Saharan Countries(BioMed Central Ltd, 2018-10-22) Mfueni, Elvire; Devleesschauwer, Brecht; Rosas-Aguirre, Angel; Van Malderen, Carine; Brandt, Patrick T.; Ogutu, Bernhards; Snow, Robert W.; Tshilolo, Leon; Zurovac, Dejan; Vanderelst, Dieter; Speybroeck, Niko; 163951331 (Brandt, PT); Brandt, Patrick T.Background: Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of malaria in children under five in the Democratic Republic of the Congo, Uganda and Kenya, using a Bayesian modelling framework that combined in a novel way malaria data from national household surveys with external information about the sensitivity and specificity of the malaria diagnostic methods used in those surveys-i.e., rapid diagnostic tests and light microscopy. Methods: Data were used from the Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS) conducted in the Democratic Republic of the Congo (DHS 2013-2014), Uganda (MIS 2014-2015) and Kenya (MIS 2015), where information on infection status using rapid diagnostic tests and/or light microscopy was available for 13,573 children. True prevalence was estimated using a Bayesian model that accounted for the conditional dependence between the two diagnostic methods, and the uncertainty of their sensitivities and specificities obtained from expert opinion. Results: The estimated true malaria prevalence was 20% (95% uncertainty interval [UI] 17%-23%) in the Democratic Republic of the Congo, 22% (95% UI 9-32%) in Uganda and 1% (95% UI 0-3%) in Kenya. According to the model estimations, rapid diagnostic tests had a satisfactory sensitivity and specificity, and light microscopy had a variable sensitivity, but a satisfactory specificity. Adding reported history of fever in the previous 14 days as a third diagnostic method to the model did not affect model estimates, highlighting the poor performance of this indicator as a malaria diagnostic. Conclusions: In the absence of a gold standard test, Bayesian models can assist in the optimal estimation of the malaria burden, using individual results from several tests and expert opinion about the performance of those tests.