1,721,050 research outputs found
Supporting Data for UPTick Project Active Tick Surveillance, 2020 to 2021
No full textThis dataset covers information collected during One Health active surveillance activities for Lyme disease research, monthly from May to October in 2020 and biweekly for the same period in 2021. In this study, we collected ticks and trapped small mammals, tested both for tick-borne pathogens, and monitored the intensity of deer foraging activity to identify the relationship of peri-urban habitat types - namely, residential, woodland, and residential-woodland interface zones - with Lyme disease risk. This dataset includes ecologcial site characteristics observed along tick drag sampling transects, recorded at GPS waypoints every 25 metres
Maternal and Child Health in Jimma Zone, Ethiopia: Predictors, Barriers and Strategies for Improvement
No full textReducing maternal and child mortality has been a top global health priority for the past two decades. Through this thesis, I underline some of the strategies, barriers and determinants to optimal maternal and child health (MCH) in three specific districts of Jimma Zone in the southwest of Ethiopia. My first paper has a particular focus on the quality of MCH data collected within the health management information system (HMIS), while the second paper focuses on the utilization of antenatal care (ANC) services, assessments of malaria in pregnancy, and women’s access to malaria preventive measures using data from a cross-sectional survey conducted in the three study districts.
The quality of MCH data collected within the HMIS from July 2014 to June 2015 for the 26 primary health care units (PHCUs) located within the three districts was evaluated using the World Health Organization’s Data Quality Report Card (DQRC). To complement the methods recommended in the DQRC, Pearson correlation coefficients, intraclass correlation coefficients, and Bland-Altman analysis were used to determine the agreement between MCH indicator coverage estimates derived from the HMIS and a population-based survey conducted with 3,784 women who had a birth outcome within the same time frame. The quality of MCH data collected within the HMIS was determined to be unsatisfactory, with many health facilities located in the three districts not reporting completely, consistently, or accurately MCH key indicators relating specifically to ANC, skilled birth attendance at delivery, and postnatal care. This finding is important since poor data quality can compromise effective decision-making and resource allocation processes aimed at contributing to better health outcomes in mothers and newborns.
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To address the objectives set in the second chapter, analysis of cross-sectional survey data from 3,784 women who had a birth outcome in the year preceding the survey was performed through logistic regression models adjusting for clustering of the participants by PHCU. While close to 85% of the women attended at least one ANC visit, less than 50% of the participants received four or more ANC visits. Lack of necessity, distance to health facility and unavailability of transportation were determined as key reasons for not attending ANC. Women who completed secondary or higher education, were from the richest households, were exposed to different media sources, and were able to make decisions about their healthcare by themselves or jointly with their husband were more likely to attend ANC services. Frequent visits by a health extension worker and pregnancy intendedness also influenced ANC attendance. Bed net ownership and utilization during last pregnancy were also relatively low (52% and 26%, respectively). The results also showed that the odds of owning and always using a mosquito net were higher in participants that attended ANC, with odds ratios of 1.98 (95% CI: 1.55-2.53) and 1.62 (95% CI: 1.23 – 2.13), respectively. The prevalence of malaria infection during pregnancy was low in our recruited sample, with 1.45% of the participants reporting suffering from malaria during their last pregnancy. We determined significant negative relationships between malaria infection and maternal age and education level.
This work emphasizes the importance of improving the quality of MCH data within the HMIS in Ethiopia as well as addressing the inequities relating to ANC attendance in Jimma Zone. Given the adverse effects that malaria can have on the progress and outcomes of a pregnancy, the importance of promoting mosquito net ownership and use as part of ANC services is also highlighted
Spatial Variation in Risk Factors for Malaria in Muleba, Tanzania
No full textDespite the rich knowledge surrounding risk factors for malaria, the spatial processes of malaria transmission and vector control interventions are underexplored. This thesis aims 1) to describe the spatial variation of risk factor effects on malaria infection, and 2) to determine the presence and range of any community effect from malaria vector control interventions. Data from a cluster-randomized control trial in Tanzania were analyzed to determine the geographically-weighted odds of malaria infection in children at trial baseline and post-intervention. The spatial range of intervention effects on malaria infection was estimated post-intervention using semivariance models. Spatial heterogeneities in malaria infection and each covariate under study were found. The median effective semivariance range of intervention effects was approximately 1200 meters, suggesting the presence of a community effect that may cause contamination between trial clusters. Trials should consider these spatial effects when examining interventions and ensure that clusters are adequately insulated from contamination
Assessing the Determinants of Maternal Healthcare Service Utilization and Effectiveness of Interventions to Improve Institutional Births in Jimma Zone, Ethiopia
No full textThe strong emphasis placed on improving equality and well-being for all in the Sustainable Development Goals underscores the importance of tackling persistent within-country disparities in maternal mortality and poor health outcomes. Addressing maternal healthcare access barriers is, thus, crucial, particularly in low-resource settings. Numerous studies investigating determinants of maternal healthcare service use in Ethiopia exist but are limited by their focus on individual and household factors, and by methodological weaknesses. A nuanced understanding of the role of socioeconomic and geographic context in influencing access to care is needed to respond effectively.
Maternity waiting homes (MWHs) are a potential strategy to address geographical barriers that delay women’s access to obstetric care. However, in addition to concerns about service quality, there is limited evidence on their effectiveness and on what models meet women’s needs. My research goals were, therefore, to contribute to the understanding of what contextual factors influence maternal healthcare service use in general; and to determine whether or not upgraded MWHs operating in an enabling environment could improve delivery care use in rural Ethiopia. My primary data sources were household surveys conducted as part of a cluster-randomized controlled trial evaluating MWHs and local leader training in Jimma Zone, Ethiopia.
Random effects multivariable logistic regression analysis of survey data brought to light the social and financial resources that facilitate MWH use, highlighting the need for complementary interventions to make access more equitable. Spatial analyses identified subnational variation in service use at a finer scale than routinely reported and unmasked local variation in the relevance and magnitude of associations between individual-, interpersonal-, and health system factors and maternal healthcare use. These findings have implications for relying upon homogenous national responses to improve equality in access to care and health outcomes. Finally, analysis of trial data found a non-significant effect of interventions on delivery care use likely due to implementation issues and extraneous factors. The need to generate strong evidence of effectiveness of MWHs in improving maternal healthcare service use using sustainable and equitable MWH models using methods appropriate for complex intervention evaluation remains
Impact of Indoor Residual Spraying and Insecticide-treated Bed Nets on Malaria Transmission in Sub-Saharan Africa Using Mathematical Modelling
No full textBackground: Malaria causes over 400,000 estimated deaths annually worldwide, with about 90% in sub-Saharan Africa. Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are two vector-control interventions proven to reduce malaria transmission, but their use together compared to separate has shown mixed results.
Methodology: We used a mathematical model to examine the impact of LLINs and IRS on malaria transmission. Time-series analyses and basic reproductive numbers (R0) were developed using MATLAB. We also assessed IRS timing and performed a sensitivity analysis on R0.
Results: Modelling scenarios combining LLINs with IRS were similar to those with LLINs alone. Shorter IRS impulses had greater reductions in mosquito populations. The LLIN feeding-inhibition rate was a key parameter with a negative correlation to R0.
Discussion/Conclusion: We developed an understanding of the effect of vector-control strategies on malaria transmission. IRS, when paired with LLINs, showed only small improvements in reducing malaria transmission compared to LLINs alone. These results can assist vector-control programmes
Impact of Indoor Residual Spraying and Insecticide-treated Bed Nets on Malaria Transmission in Sub-Saharan Africa Using Mathematical Modelling
No full textBackground: Malaria causes over 400,000 estimated deaths annually worldwide, with about 90% in sub-Saharan Africa. Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are two vector-control interventions proven to reduce malaria transmission, but their use together compared to separate has shown mixed results.\ud
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Methodology: We used a mathematical model to examine the impact of LLINs and IRS on malaria transmission. Time-series analyses and basic reproductive numbers (R0) were developed using MATLAB. We also assessed IRS timing and performed a sensitivity analysis on R0.\ud
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Results: Modelling scenarios combining LLINs with IRS were similar to those with LLINs alone. Shorter IRS impulses had greater reductions in mosquito populations. The LLIN feeding-inhibition rate was a key parameter with a negative correlation to R0.\ud
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Discussion/Conclusion: We developed an understanding of the effect of vector-control strategies on malaria transmission. IRS, when paired with LLINs, showed only small improvements in reducing malaria transmission compared to LLINs alone. These results can assist vector-control programmes
The Spatial and Molecular Epidemiology of Lyme Disease in Eastern Ontario
No full textLyme disease is an emerging tick-borne illness in Canada, with human case numbers increasing 15- to 20-fold since Lyme disease became nationally notifiable in 2009 until the present. In Ontario, Canada's largest province by population, average Lyme disease incidence across the province is similar to that of national estimates. However, in eastern Ontario, which is near tick endemic regions in the northeastern Unites States, Lyme disease incidence is disproportionately higher compared to the rest of the province.
The objectives of this thesis are to identify environmental Lyme disease risk areas in Ontario, to explore spatiotemporal trends in Lyme disease emergence, and to identify neighbourhood-level socioecological risk factors for Lyme disease. In addition, this thesis also aims to assess the risk of other tick-borne illnesses that are transmitted by the blacklegged tick, Ixodes scapularis, which is also the main vector for Lyme disease in Canada.
Using maximum entropy species distribution modelling to correlate blacklegged tick occurrence data with environmental variables, predictive risk models for I. scapularis and the Lyme disease pathogen, Borrelia burgdorferi, were developed. The model prediction was used to classify low and high environment risk areas and, using a case-control epidemiological study, we assessed that residence in risk areas was a strong predictor of Lyme disease. However, this relationship was modulated by socioecological factors linked to higher overall rurality of the locality of home residence. Spatial cluster analyses further revealed that human Lyme disease cases clustered in regions with the high numbers of reported B. burgdorferi-infected ticks in the environment. Many individuals residing in large metropolitan regions, like the City of Ottawa, reported tick exposures outside their public health unit of residence; however, local clusters of Lyme disease were also detected in suburban regions near conservation areas, trails, and urban woodlands. The prevalence of other tick-borne pathogens was low, although several pathogens of public health significance including Borrelia miyamotoi and Anaplasma phagocytophilum were detected at multiple sites surveyed for ticks between 2017-2021.
Overall, this thesis identify patterns in Lyme disease emergence (and potentially other tick-borne illnesses), defines environmental risk areas for Lyme disease in Ontario, and highlights important socioecological risk factors for Lyme disease in eastern Ontario
Modelling Human Risk of West Nile Virus Using Surveillance and Environmental Data
No full textLimited research has been performed in Ontario to ascertain risk factors for West Nile Virus (WNV) and to develop a unified risk prediction strategy. The aim of the current body of work was to use spatio-temporal modelling in conjunction with surveillance and environmental data to determine which pre-WNV season factors could forecast a high risk season and to explore how well mosquito surveillance data could predict human cases in space and time during the WNV season. Generalized linear mixed modelling found that mean minimum monthly temperature variables and annual WNV-positive mosquito pools were most significantly predictive of number of human WNV cases (p<0.001). Spatio-temporal cluster analysis found that positive mosquito pool clusters could predict human case clusters up to one month in advance. These results demonstrate the usefulness of mosquito surveillance data as well as publicly available climate data for assessing risk and informing public health practice
Modelling Human Risk of West Nile Virus Using Surveillance and Environmental Data
No full textLimited research has been performed in Ontario to ascertain risk factors for West Nile Virus (WNV) and to develop a unified risk prediction strategy. The aim of the current body of work was to use spatio-temporal modelling in conjunction with surveillance and environmental data to determine which pre-WNV season factors could forecast a high risk season and to explore how well mosquito surveillance data could predict human cases in space and time during the WNV season. Generalized linear mixed modelling found that mean minimum monthly temperature variables and annual WNV-positive mosquito pools were most significantly predictive of number of human WNV cases (p<0.001). Spatio-temporal cluster analysis found that positive mosquito pool clusters could predict human case clusters up to one month in advance. These results demonstrate the usefulness of mosquito surveillance data as well as publicly available climate data for assessing risk and informing public health practice
Identifying Comorbid Risk Factors of West Nile Neuroinvasive Disease in the Ontario Population, 2002-2012, Using Laboratory and Health Administrative Data
No full textBackground/Objectives:
West Nile neuroinvasive disease (WNND) is a severe neurological illness that develops in approximately 1% of individuals infected with West Nile virus (WNV). Manifesting most frequently as encephalitis (WNE), meningitis (WNM), or acute flaccid paralysis (WNP), there is no cure for WNND beyond supportive care and rehabilitation, and death or permanent disability are common outcomes. As the virus arrived in North America less than 20 years ago, determinants of severe disease progression following infection are still being explored. This project is the first to examine comorbid conditions as risk factors of WNND in Ontario using a population-based study design. As prevention is the only avenue of defence against WNND, identifying comorbid risk factors of WNND would allow for public health prevention campaigns targeted to high-risk groups. The main objectives of this thesis were to explore whether pre-existing chronic diseases were associated with the development of WNND, or any of its three manifestations (i.e., encephalitis, meningitis, acute flaccid paralysis).
Methods:
This was a retrospective, population-based study including all Ontario residents with a confirmed diagnosis of WNV infection between January 1, 2002 and December 31, 2012. A cohort of individuals with WNV was identified from a provincial laboratory database and individually-linked to health administrative databases. In the WNV cohort, individuals with WNND and 13 comorbid conditions were identified using algorithms based on ICD-10-CA diagnostic codes. Incidence of WNND following WNV infection was then compared among individuals with and without comorbid conditions using relative risks estimated by log binomial regression. Additionally, risk ratios were calculated for associations between specific comorbid conditions and WNND neuroinvasive manifestation (i.e., encephalitis, meningitis, acute flaccid paralysis). Finally, associations between Charlson Comorbidity Index (CCI) scoring and development of WNND was examined through calculation of relative risk using log binomial regression.
Results/Potential Impact:
Risk factors for WNND included male sex (aRR: 1.21; 95% CI: 1.00-1.46) in addition to the combined effect of hypertension and increasing age (5-year intervals) (aRR: 1.16; 95% CI: 1.08-1.24); WNND was also associated with increasing CCI scores; individuals in low, medium, and high categories had increased risk compared to individuals with a score of zero, but the greatest risk was in the high CCI category (aRR: 3.45; 95% CI: 2.25-4.83) Male sex (aRR: 1.32; 95% CI: 1.00-1.76), increasing age (aRR: 1.02; 95% CI: 1.02-1.03), and being immunocompromised (aRR: 2.61; 95% CI: 1.23-4.53) were associated with development of WNE. No risk factors were identified for WNM and WNP. Identification of comorbid risk factors of WNND will allow public health officials to identify high-risk groups and to develop prevention strategies targeted for vulnerable individuals
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