Plasmodium falciparum AMA1 and CSP antigen diversity in parasite isolates from southern Ghana.

Introduction: Diversity in malarial antigens is an immune evasion mechanism that gives malaria parasites an edge over the host. Immune responses against one variant of a polymorphic antigen are usually not fully effective against other variants due to altered epitopes. This study aimed to evaluate diversity in the Plasmodium falciparum antigens apical membrane antigen 1 (PfAMA1) and circumsporozoite protein (PfCSP) from circulating parasites in a malaria-endemic community in southern Ghana and to determine the effects of polymorphisms on antibody response specificity. Methods: The study involved 300 subjects, whose P. falciparum infection status was determined by microscopy and PCR. Diversity within the two antigens was evaluated by msp2 gene typing and molecular gene sequencing, while the host plasma levels of antibodies against PfAMA1, PfCSP, and two synthetic 24mer peptides from the conserved central repeat region of PfCSP, were measured by ELISA. Results: Of the 300 subjects, 171 (57%) had P. falciparum infection, with 165 of the 171 (96.5%) being positive for either or both of the msp2 allelic families. Gene sequencing of DNA from 55 clonally infected samples identified a total of 56 non-synonymous single nucleotide polymorphisms (SNPs) for the Pfama1 gene and these resulted in 44 polymorphic positions, including two novel positions (363 and 365). Sequencing of the Pfcsp gene from 69 clonal DNA samples identified 50 non-synonymous SNPs that resulted in 42 polymorphic positions, with half (21) of these polymorphic positions being novel. Of the measured antibodies, only anti-PfCSP antibodies varied considerably between PCR parasite-positive and parasite-negative persons. Discussion: These data confirm the presence of a considerable amount of unique, previously unreported amino acid changes, especially within PfCSP. Drivers for this diversity in the Pfcsp gene do not immediately seem apparent, as immune pressure will be expected to drive a similar level of diversity in the Pfama1 gene.

Predicting COVID-19 hospitalizations: The importance of healthcare hotlines, test positivity rates and vaccination coverage.

In this study, we developed a negative binomial regression model for one-week ahead spatio-temporal predictions of the number of COVID-19 hospitalizations in Uppsala County, Sweden. Our model utilized weekly aggregated data on testing, vaccination, and calls to the national healthcare hotline. Variable importance analysis revealed that calls to the national healthcare hotline were the most important contributor to prediction performance when predicting COVID-19 hospitalizations. Our results support the importance of early testing, systematic registration of test results, and the value of healthcare hotline data in predicting hospitalizations. The proposed models may be applied to studies modeling hospitalizations of other viral respiratory infections in space and time assuming count data are overdispersed. Our suggested variable importance analysis enables the calculation of the effects on the predictive performance of each covariate. This can inform decisions about which types of data should be prioritized, thereby facilitating the allocation of healthcare resources.

Evolution of spatial disease clusters via a Bayesian space-time variability modelling.

This study proposes to use exceedance posterior probabilities of a space-time random-effects model to study the temporal dynamics of clusters. The local time trends specified for each area is further smoothed over space. We modelled the common spatial and the space-varying temporal trend using a multivariate Markov Random field to incorporate within-area correlations. We estimate the model parameters within a fully Bayesian framework. The exceedance posterior probabilities are further used to classify the common spatial trend into hot-spots, cold-spots, and neutral-spots. The local time trends are classified into increasing, decreasing, and stable trends. The results is a 3×3 table depicting the time trends within clusters. As a demonstration, we apply the proposed methodology to study the evolution of spatial clustering of intestinal parasite infections in Ghana. We find the methodology presented in this paper applicable and extendable to other or multiple tropical diseases which may have different space-time conceptualizations.

Geospatial Health (GeoHealth): Current Trends, Methods, and Applications.

As an emerging field, Geospatial Health (GeoHealth) integrates geospatial technologies, (spatial) epidemiology, and health services/resource allocations (health accessibility), with a focus to fight the burden of diseases [...].

World Hepatitis day 2021 -screening and vaccination against Hepatitis B virus in Accra, Ghana.

BACKGROUND: In Ghana, Hepatitis B virus (HBV) infection remains a major public health threat as in many parts of the world. Even with an effective vaccine, there are shortfalls with low vaccine coverage among adults. To create awareness and encourage vaccination, community engagement and public-private partnerships are needed in endemic settings to help fund campaigns and offer screening and vaccinations at no cost to under privileged people. OBJECTIVES: An awareness and screening exercise was scheduled by University of Ghana-based Hepatitis-Malaria (HEPMAL) project team to coincide with the World Hepatitis Day (WHD) 2021. It was to engage the community in creating awareness of the menace and offer diagnostic services to ascertain prevalence levels and provide needed clinical support. METHODS: Participants from the University of Ghana community and its immediate environs were registered, taken through pre-counselling sessions where they were educated on hepatitis transmission and prevention before consenting. Eligible participants were screened for HBV markers (HBsAg, HBeAg, HBsAb, HBcAb,HbcAg) with a rapid test kit. All HBsAb-negative participants were recommended for initial vaccination at the event, whilst the subsequent shots were administered at the University Hospital Public Health Department. Hepatitis B surface Antigen-positive participants were counselled and referred for appropriate care. RESULTS: / Outcomes: A total of 297 people, comprising of 126 (42%) males and 171 (58%) females aged between 17 and 67 years were screened during the exercise. Amongst these, 246 (82.8%) showed no detectable protective antibodies against HBV and all of them agreed to and were given the first dose HBV vaccine. Additionally, 19 (6.4%) individuals tested positive for HBsAg and were counselled and referred to specialists from the University Hospital for further assessment and management. We found that 59 (19.9%) of our participants had previously initiated HBV vaccination and had taken at least one dose of the vaccine more than 6 months prior to this screening, 3 of whom tested positive for HBsAg. For the three-dose HBV vaccines deployed, a little over 20% (50/246) and a further 17% (33/196) did not return for the second and the third doses respectively, resulting in an overall 66% (163/246) of persons who completed all three vaccinations. CONCLUSIONS: / Lessons learnt: Our medical campaign exercise established an active case prevalence rate of 6.4% and achieved a full vaccination success rate of 66% which is critical in the induction of long-term immunity in the participants. Aside these achievements, we would like to reiterate the importance of the use of different approaches including educational events and WHD activities to target groups and communities to raise awareness. Additionally, home and school vaccination programmes may be adopted to enhance vaccine uptake and adherence to the vaccination schedule. We plan to extend this screening exercise to deprived and/or rural communities where HBV incidence may be higher than in urban communities.

Comparison of the association between different ozone indicators and daily respiratory hospitalization in Guangzhou, China.

Background: Epidemiological studies have widely proven the impact of ozone (O3) on respiratory mortality, while only a few studies compared the association between different O3 indicators and health. Methods: This study explores the relationship between daily respiratory hospitalization and multiple ozone indicators in Guangzhou, China, from 2014 to 2018. It uses a time-stratified case-crossover design. Sensitivities of different age and gender groups were analyzed for the whole year, the warm and the cold periods. We compared the results from the single-day lag model and the moving average lag model. Results: The results showed that the maximum daily 8 h average ozone concentration (MDA8 O3) had a significant effect on the daily respiratory hospitalization. This effect was stronger than for the maximum daily 1 h average ozone concentration (MDA1 O3). The results further showed that O3 was positively associated with daily respiratory hospitalization in the warm season, while there was a significantly negative association in the cold season. Specifically, in the warm season, O3 has the most significant effect at lag 4 day, with the odds ratio (OR) equal to 1.0096 [95% confidence intervals (CI): 1.0032, 1.0161]. Moreover, at the lag 5 day, the effect of O3 on the 15-60 age group was less than that on people older than 60 years, with the OR value of 1.0135 (95% CI: 1.0041, 1.0231) for the 60+ age group; women were more sensitive than men to O3 exposure, with an OR value equal to 1.0094 (95% CI: 0.9992, 1.0196) for the female group. Conclusion: These results show that different O3 indicators measure different impacts on respiratory hospitalization admission. Their comparative analysis provided a more comprehensive insight into exploring associations between O3 exposure and respiratory health.

The "Nitrogen Effect": Complexation with Macrocycles Potentiates Fused Heterocycles to Form Halogen Bonds in Competitive Solvents.

Weak intermolecular forces are typically very difficult to observe in highly competitive polar protic solvents as they are overwhelmed by the quantity of competing solvent. This is even more challenging for three-component ternary assemblies of pure organic compounds. In this work, we overcome these complications by leveraging the binding of fused aromatic N-heterocycles in an open resorcinarene cavity to template the formation of a three-component halogen-bonded ternary assembly in a protic polar solvent system.

Short-term health impacts related to ozone in China before and after implementation of policy measures: A systematic review and meta-analysis.

This paper presents a meta-analysis of the impacts of short-term exposure to ozone (O3) on three health endpoints: all-cause, cardiovascular, and respiratory mortality in China. All relevant studies from January 1990 to December 2021 were searched from four databases. After screening, 30 studies were included for the meta-analysis. The results showed that a significant rise of 0.41 % (95 % confidence interval (CI): 0.35 %-0.48 %) in all-cause, 0.60 % (95 % CI: 0.51 %-0.68 %) in cardiovascular and 0.45 % (95 % CI: 0.28 %-0.62 %) in respiratory mortality for each 10 µg m-3 increase in the maximum daily 8 h average O3 concentration (MDA8 O3). Moreover, results stratified by heterogeneous time periods before and after implementing a policy measure in 2013, showed that the pooled effects for all-cause and respiratory mortality before were greater than those after, while the pooled effects for cardiovascular mortality before 2013 were slightly smaller than those after. The finding that short-term exposure to O3 was positively related to the three health endpoints was validated by means of a sensitivity analysis. Furthermore, we did not observe any publication bias. Our results present an updated and better understanding of the relationship between short-term exposure to O3 and the three health endpoints, while providing a reference for further assessment of the impact of short-term O3 exposure on human health.

Bayesian geostatistical modelling of stunting in Rwanda: risk factors and spatially explicit residual stunting burden.

BACKGROUND: Stunting remains a significant public health issue in Rwanda and its prevalence exhibits considerable geographical variation. We apply Bayesian geostatistical modelling to study the spatial pattern of stunting in children less than five years considering anthropometric, socioeconomic and demographic risk factors in Rwanda. In addition, we predict the spatial residuals effects to quantify the burden of stunting not accounted for by our geostatistical model. METHODS: We used the data from the 2015 Rwanda Demographic and Health Survey. We fitted two spatial logistic models with similar structures, only differentiated by the inclusion or exclusion of spatially structured random effects. RESULTS: The risk factors of stunting identified in the geostatistical model were being male (OR = 1.32, 95% CI: 1.16, 1.47), lower birthweight (kg) (OR = 0.96, 95% CI: 0.95, 0.97), non-exclusive breastfeeding (OR = 1.24, 95% CI: 1.04, 1.45), occurrence of diarrhoea in the last two weeks (OR = 1.18, 95% CI: 1.02, 1.37), a lower proportion of mothers with overweight (BMI ≥ 25) (OR = 0.82, 95% CI: 0.71, 0.95), a higher proportion of mothers with no or only primary education (OR = 1.14, 95% CI: 0.99, 1.36). Also, a higher probability of living in a house with poor flooring material (OR = 1.22, 95% CI: 1.06, 1.41), reliance on a non-improved water source (OR = 1.13, 95% CI: 1.00, 1.27), and a low wealth index were identified as risk factors of stunting. Mapping of the spatial residuals effects showed that, in particular, the Northern and Western regions, followed by the Southern region of Rwanda, still exhibit a higher risk of stunting even after accounting for all the covariates in the spatial model. CONCLUSIONS: Further studies are needed to identify the still unknown spatially explicit factors associated with higher risk of stunting. Finally, given the spatial heterogeneity of stunting, interventions to reduce stunting should be geographically targeted.

A 2-Month-Old with Kawasaki Disease with Coronary Artery Dilation in the Pre-COVID-19 Era.

BACKGROUND Kawasaki disease (KD) is an acute inflammatory vasculitis, which occurs mostly in childhood, predominantly between the ages of 6 months and 5 years. The incidence of coronary artery abnormalities associated with KD has decreased from 25% to 4% as a result of timely diagnosis and treatment with intravenous immunoglobulin (IVIG). Infants ≤6 months of age are the most likely to develop prolonged fever without the other clinical criteria for KD, and diagnosis can sometimes be challenging or delayed. They are therefore at particularly high risk of developing coronary artery abnormalities. CASE REPORT A 2-month-old male infant with no significant medical history initially presented with a history of nasal congestion, right conjunctivitis, red lips, and 1 loose stool in the pre-COVID-19 era. He was diagnosed with otitis media and was started on oral amoxicillin. By day 7 of fever, he had developed symptoms and signs and laboratory findings consistent with Kawasaki disease, which is rare in this age group. His echocardiogram showed dilated proximal left anterior descending and right coronary arteries. He was successfully treated, and his most recent echocardiogram, performed 17 months after his treatment, showed remarkable improvement in the coronary arteries. CONCLUSIONS Kawasaki disease in children less than 6 months of age is still rare, and the presentation can sometimes make the diagnosis somewhat challenging. Increased clinical suspicion is required for recognition in the youngest patients, as they are more likely to present with few features of KD. Early diagnosis and treatment are needed to prevent or minimize the risk of significant coronary artery abnormalities.

Spatial variation in lymphatic filariasis risk factors of hotspot zones in Ghana.

BACKGROUND: Lymphatic Filariasis (LF), a parasitic nematode infection, poses a huge economic burden to affected countries. LF endemicity is localized and its prevalence is spatially heterogeneous. In Ghana, there exists differences in LF prevalence and multiplicity of symptoms in the country's northern and southern parts. Species distribution models (SDMs) have been utilized to explore the suite of risk factors that influence the transmission of LF in these geographically distinct regions. METHODS: Presence-absence records of microfilaria (mf) cases were stratified into northern and southern zones and used to run SDMs, while climate, socioeconomic, and land cover variables provided explanatory information. Generalized Linear Model (GLM), Generalized Boosted Model (GBM), Artificial Neural Network (ANN), Surface Range Envelope (SRE), Multivariate Adaptive Regression Splines (MARS), and Random Forests (RF) algorithms were run for both study zones and also for the entire country for comparison. RESULTS: Best model quality was obtained with RF and GBM algorithms with the highest Area under the Curve (AUC) of 0.98 and 0.95, respectively. The models predicted high suitable environments for LF transmission in the short grass savanna (northern) and coastal (southern) areas of Ghana. Mainly, land cover and socioeconomic variables such as proximity to inland water bodies and population density uniquely influenced LF transmission in the south. At the same time, poor housing was a distinctive risk factor in the north. Precipitation, temperature, slope, and poverty were common risk factors but with subtle variations in response values, which were confirmed by the countrywide model. CONCLUSIONS: This study has demonstrated that different variable combinations influence the occurrence of lymphatic filariasis in northern and southern Ghana. Thus, an understanding of the geographic distinctness in risk factors is required to inform on the development of area-specific transmission control systems towards LF elimination in Ghana and internationally.

Modeling schistosomiasis spatial risk dynamics over time in Rwanda using zero-inflated Poisson regression.

The recorded clinical cases of S. mansoni at primary health facility level contain an excessive number of zero records. This could mean that no S. mansoni infection occurred (a true zero) in the health facility service area but it could also that at least one infection occurred but none were reported or diagnosed (a false zero). Standard statistical analysis, using exploratory or confirmatory spatial regression, fail to account for this type of data insufficiency. This study developed a zero-inflated Poisson model to explore the spatiotemporal variation in schistosomiasis risk at a fine spatial scale. We used environmental data generated at primary health facility service area level as explanatory variables affecting transmission risk. Identified risk factors were subsequently used to project the spatial variability of S. mansoni infection risk for 2050. The zero-inflated Poisson model shows a considerable increase of relative risk of the schistosomiasis over one decade. Furthermore, the changes between the risk in 2009 and forecasted risk by 2050 indicated both persistent and emerging areas with high relative risk of schistosomiasis infection. The risk of schistosomiasis transmission is 69%, 29%, and 50% higher in areas with rice cultivation, proximity to rice farms, and proximity to a water body respectively. The prediction and forecasting maps provide a valuable tool for monitoring schistosomiasis risk in Rwanda and planning future disease control initiatives in wetland ecosystem development context.

Bayesian analysis of the short-term association of NO2 exposure with local burden of asthmatic symptoms in children.

Short-term exposure to air pollution has been associated with exacerbation of respiratory diseases such as asthma. Substantial heterogeneity in effect estimates has been observed between previous studies. This study aims to quantify the local burden of daily asthma symptoms in asthmatic children in a medium-sized city. Air pollution exposure was estimated using the nearest sensor in a fine resolution urban air quality sensor network in the city of Eindhoven, the Netherlands. Bayesian estimates of the exposure response function were obtained by updating a priori information from a meta-analysis with data from a panel study using a daily diary. Five children participated in the panel study, resulting in a total of 400 daily diary records. Positive associations between NO2 and lower respiratory symptoms and medication use were observed. The odds ratio for any lower respiratory symptoms was 1.07 (95% C.I. 0.92, 1.28) expressed per 10 µg m-3 for current day NO2 concentration, using data from the panel study only (uninformative prior). Odds ratios for dry cough and phlegm were close to unity. The pattern of associations agreed well with the updated meta-analysis. The meta-analytic random effects summary estimate was 1.05 (1.02, 1.07) for LRS. Credible intervals substantially narrowed when adding prior information from the meta-analysis. The odds ratio for lower respiratory symptoms with an informative prior was 1.06 (0.99, 1.14). Burden of disease maps showed a strong spatial variability in the number of asthmatic symptoms associated with ambient NO2 derived from a regression kriging model. In total, 70 cases of asthmatic symptoms can daily be associated with NO2 exposure in the city of Eindhoven. We conclude that Bayesian estimates are useful in estimation of specific local air pollution effect estimates and subsequent local burden of disease calculations. With the fine resolution air quality network, neighborhood-specific burden of asthmatic symptoms was assessed.

Modelling the impact of MAUP on environmental drivers for Schistosoma japonicum prevalence.

BACKGROUND: The modifiable areal unit problem (MAUP) arises when the support size of a spatial variable affects the relationship between prevalence and environmental risk factors. Its effect on schistosomiasis modelling studies could lead to unreliable parameter estimates. The present research aims to quantify MAUP effects on environmental drivers of Schistosoma japonicum infection by (i) bringing all covariates to the same spatial support, (ii) estimating individual-level regression parameters at 30 m, 90 m, 250 m, 500 m and 1 km spatial supports, and (iii) quantifying the differences between parameter estimates using five models. METHODS: We modelled the prevalence of Schistosoma japonicum using sub-provinces health outcome data and pixel-level environmental data. We estimated and compared regression coefficients from convolution models using Bayesian statistics. RESULTS: Increasing the spatial support to 500 m gradually increased the parameter estimates and their associated uncertainties. Abrupt changes in the parameter estimates occur at 1 km spatial support, resulting in loss of significance of almost all the covariates. No significant differences were found between the predicted values and their uncertainties from the five models. We provide suggestions to define an appropriate spatial data structure for modelling that gives more reliable parameter estimates and a clear relationship between risk factors and the disease. CONCLUSIONS: Inclusion of quantified MAUP effects was important in this study on schistosomiasis. This will support helminth control programmes by providing reliable parameter estimates at the same spatial support and suggesting the use of an adequate spatial data structure, to generate reliable maps that could guide efficient mass drug administration campaigns.

Bayesian Random Effect Modeling for analyzing spatial clustering of differential time trends of diarrhea incidences.

In 2012, nearly 644,000 people died from diarrhea in sub-Saharan Africa. This is a significant obstacle towards the achievement of the Sustainable Development Goal 3 of ensuring a healthy life and promoting the wellbeing at all ages. To enhance evidence-based site-specific intervention and mitigation strategies, especially in resource-poor countries, we focused on developing differential time trend models for diarrhea. We modeled the logarithm of the unknown risk for each district as a linear function of time with spatially varying effects. We induced correlation between the random intercepts and slopes either by linear functions or bivariate conditional autoregressive (BiCAR) priors. In comparison, models which included correlation between the varying intercepts and slopes outperformed those without. The convolution model with the BiCAR correlation prior was more competitive than the others. The inclusion of correlation between the intercepts and slopes provided an epidemiological value regarding the response of diarrhea infection dynamics to environmental factors in the past and present. We found diarrhea risk to increase by 23% yearly, a rate far exceeding Ghana's population growth rate of 2.3%. The varying time trends widely varied and clustered, with the majority of districts with at least 80% chance of their rates exceeding the previous years. These findings can be useful for active site-specific evidence-based planning and interventions for diarrhea.

Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection.

Understanding the spatially varying effects of demographic factors on the spatio-temporal variation of intestinal parasites infections is important for public health intervention and monitoring. This paper presents a hierarchical Bayesian spatially varying coefficient model to evaluate the effects demographic factors on intestinal parasites morbidities in Ghana. The modeling relied on morbidity data collected by the District Health Information Management Systems. We developed Poisson and Poisson-gamma spatially varying coefficient models. We used the demographic factors, unsafe drinking water, unsafe toilet, and unsafe liquid waste disposal as model covariates. The models were fitted using the integrated nested Laplace approximations (INLA). The overall risk of intestinal parasites infection was estimated to be 10.9 per 100 people with a wide spatial variation in the district-specific posterior risk estimates. Substantial spatial variation of increasing multiplicative effects of unsafe drinking water, unsafe toilet, and unsafe liquid waste disposal occurs on the variation of intestinal parasites risk. The structured residual spatial variation widely dominates the unstructured component, suggesting that the unaccounted-for risk factors are spatially continuous in nature. The study concludes that both the spatial distribution of the posterior risk and the associated exceedance probability maps are essential for monitoring and control of intestinal parasites.

Modeling Schistosoma japonicum Infection under Pure Specification Bias: Impact of Environmental Drivers of Infection.

Uncertainties in spatial modeling studies of schistosomiasis (SCH) are relevant for the reliable identification of at-risk populations. Ecological fallacy occurs when ecological or group-level analyses, such as spatial aggregations at a specific administrative level, are carried out for an individual-level inference. This could lead to the unreliable identification of at-risk populations, and consequently to fallacies in the drugs' allocation strategies and their cost-effectiveness. A specific form of ecological fallacy is pure specification bias. The present research aims to quantify its effect on the parameter estimates of various environmental covariates used as drivers for SCH infection. This is done by (i) using a spatial convolution model that removes pure specification bias, (ii) estimating group and individual-level covariate regression parameters, and (iii) quantifying the difference between the parameter estimates and the predicted disease outcomes from the convolution and ecological models. We modeled the prevalence of Schistosoma japonicum using group-level health outcome data, and city-level environmental data as a proxy for individual-level exposure. We included environmental data such as water and vegetation indexes, distance to water bodies, day and night land surface temperature, and elevation. We estimated and compared the convolution and ecological model parameter estimates using Bayesian statistics. Covariate parameter estimates from the convolution and ecological models differed between 0.03 for the nearest distance to water bodies (NDWB), and 0.28 for the normalized difference water index (NDWI). The convolution model presented lower uncertainties in most of the parameter estimates, except for NDWB. High differences in uncertainty were found in night land surface temperature (0.23) and elevation (0.13). No significant differences were found between the predicted values and their uncertainties from both models. The proposed convolution model is able to correct for a pure specification bias by presenting less uncertain parameter estimates. It shows a good predictive performance for the mean prevalence values and for a positive number of infected people. Further research is needed to better understand the spatial extent and support of analysis to reliably explore the role of environmental variables.

Assessment of a novel radiation reduction protocol for pediatric and adult congenital device implantation.

PURPOSE: Device implantation requires fluoroscopic guidance, which carries inherent risks of ionizing radiation. We evaluated the impact of a low-dose fluoroscopic protocol on radiation exposure during device implantation. METHODS: All patients who underwent pacemaker or ICD implantation with new transvenous leads from July 2011 to January 2018 were included. A novel ALARA protocol consisting of ultra-low frame rates (2-3 frames/s), low dose/frame (6-18 mGy/frame), and use of the "air-gap" technique in patients < 20 kg was employed. Demographics, procedural data, and radiation exposure levels were collected and analyzed. RESULTS: Thirty patients underwent device implantation without additional catheterization, electrophysiology study, or ablation procedure (median age 15 years; range 5-50) with a total of 43 leads placed. Forty-seven percent of patients had a primary rhythm disturbance, 33% had cardiomyopathy, and 20% had congenital heart disease. Fifty percent were pacemakers (53% dual-chamber, 27% ventricle, 20% atrial) and 50% of devices implanted were ICDs (87% single-chamber). All implants were acutely successful with acceptable atrial and ventricular sensing and capture thresholds. The median fluoroscopy time was 11.5 min (inter-quartile range (IQR) 8.0-18.2), median air kerma dose 4.0 mGy (IQR 2.5-19.5), and median dose-area product 27.8 µGy/m2 (IQR 17.1-106.5). Median implant procedure time was 133 min. One patient required revision secondary to device migration without lead derangement 2 days post-procedure. CONCLUSIONS: Use of a novel fluoroscopic protocol may help decrease radiation exposure to patients and staff without affecting efficacy or risk. These data may represent benchmarks against which future device implantation procedures can be compared.

Temporal trend and spatial clustering of cholera epidemic in Kumasi-Ghana.

Knowledge of the temporal trends and spatial patterns will have significant implications for effective preparedness in future epidemics. Our objective was to investigate the temporal trends and the nature of the spatial interaction of cholera incidences, dwelling on an outbreak in the Kumasi Metropolis, Ghana. We developed generalized nonparametric and segmented regression models to describe the epidemic curve. We used the pair correlation function to describe the nature of spatial clustering parameters such as the maximum scale of interaction and the scale of maximal interaction. The epidemic rose suddenly to a peak with 40% daily increments of incidences. The decay, however, was slower with 5% daily reductions. Spatial interaction occurred within 1 km radius. Maximal interaction occurred within 0.3 km, suggesting a household level of interactions. Significant clustering during the first week suggests secondary transmissions sparked the outbreak. The nonparametric and segmented regression models, together with the pair correlation function, contribute to understanding the transmission dynamics. The issue of underreporting remains a challenge we seek to address in future. These findings, however, will have innovative implications for developing preventive measures during future epidemics.