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Background: Reactive case detection (RCD) seeks to enhance malaria surveillance and control by identifying and treating parasitaemic individuals residing near index cases. In Zambia, this strategy starts with passive detection of symptomatic incident malaria cases at local health facilities or by community health workers, with subsequent home visits to screen-and-treat residents in the index case and neighbouring (secondary) households within a 140-m radius using rapid diagnostic tests (RDTs). However, a small circular radius may not be the most efficient strategy to identify parasitaemic individuals in low-endemic areas with hotspots of malaria transmission. To evaluate if RCD efficiency could be improved by increasing the probability of identifying parasitaemic residents, environmental risk factors and a larger screening radius (250 m) were assessed in a region of low malaria endemicity. Methods: Between January 12, 2015 and July 26, 2017, 4170 individuals residing in 158 index and 531 secondary households were enrolled and completed a baseline questionnaire in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia. Plasmodium falciparum prevalence was measured using PfHRP2 RDTs and quantitative PCR (qPCR). A Quickbird™ high-resolution satellite image of the catchment area was used to create environmental risk factors in ArcGIS, and generalized estimating equations were used to evaluate associations between risk factors and secondary households with parasitaemic individuals. Results: The parasite prevalence in secondary (non-index case) households was 0.7% by RDT and 1.8% by qPCR. Overall, 8.5% (n = 45) of secondary households had at least one resident with parasitaemia by qPCR or RDT. The risk of a secondary household having a parasitaemic resident was significantly increased in proximity to higher order streams and marginally with increasing distance from index households. The adjusted OR for proximity to third- and fifth-order streams were 2.97 (95% CI 1.04–8.42) and 2.30 (95% CI 1.04–5.09), respectively, and that for distance to index households for each 50 m was 1.24 (95% CI 0.98–1.58). Conclusion: Applying proximity to streams as a screening tool, 16% (n = 3) more malaria-positive secondary households were identified compared to using a 140-m circular screening radius. This analysis highlights the potential use of environmental risk factors as a screening strategy to increase RCD efficiency. [ABSTRACT FROM AUTHOR]

Background: Despite large reductions in malaria burden across Zambia, some regions continue to experience extremely high malaria transmission. In Nchelenge District, Luapula Province, northern Zambia, almost half the human population carries parasites. Intervention coverage has increased substantially over the past decade, but comprehensive district-wide entomological studies to guide delivery of vector control measures are lacking. This study describes the bionomics and spatio-temporal patterns of malaria vectors in Nchelenge over a two and a half year period, investigates what household factors are associated with high vector densities and determines why vector control may not have been effective in the past to better guide future control efforts. Methods: Between April 2012 and September 2014, twenty-seven households from across Nchelenge District were randomly selected for monthly light trap collections of mosquitoes. Anopheline mosquitoes were identified morphologically and molecularly to species. Foraging rates were estimated and sporozoite rates were determined by circumsporozoite ELISAs to calculate annual entomological inoculation rates. Blood feeding rates and host preference were determined by PCR. Zero-inflated negative binomial models measured environmental and household factors associated with mosquito abundance at study households such as season, proximity to the lake, and use of vector control measures. Results: The dominant species in Nchelenge was An. funestus (s.s.) with An. gambiae (s.s.) as a secondary vector. Both vectors were found together in large numbers across the district and the combined EIRs of the two vectors exceeded 80 infectious bites per person per annum. An. funestus household densities increased in the dry season whilst An. gambiae surged during the rains. Presence of insecticide treated nets (ITNs) and closed eaves in the houses were found to be associated with fewer numbers of An. gambiae but not An. funestus. There was no association with indoor residual spraying (IRS). Conclusion: In Nchelenge, the co-existence of two highly anthropophagic vectors, present throughout the year, is likely to be driving the high malaria transmission evident in the district. The vectors here have been shown to be highly resistant to pyrethroids used for IRS during the study. Vector control interventions in this area would have to be multifaceted and district-wide for effective control of malaria. [ABSTRACT FROM AUTHOR]

Background: Reactive case detection (RACD) for malaria is a strategy that may be used to complement passive surveillance, as passive surveillance fails to identify infections that are asymptomatic or do not seek care. The spatial and seasonal patterns of incident (index) cases reported at a single clinic in Chongwe District were explored. Methods: A RACD strategy was implemented from June 2012 to June 2013 in a single catchment area in Chongwe District. Incident (index) cases recorded at the clinic were followed up at their household, and all household contacts were tested for malaria using rapid diagnostic tests (RDTs). GPS coordinates were taken at each index household. Spatial analyses were conducted to assess characteristics related to clustering, cluster detection and spatial variation in risk of index houses. Effects of season (rainy versus dry), distance to the clinic and distance to the main road were considered as modifying factors. Lastly, logistic regression was used to identify factors associated with the proportion of household contacts testing RDT positive. Results: A total of 426 index households were enrolled, with 1,621 household contacts (45% RDT positive). Two space-time clusters were identified in the rainy season, with ten times and six times higher risk than expected. Significantly increased spatial clustering of index households was found in the rainy season as compared to the dry season (based on K-function methodology). However, no seasonal difference in mapped spatial intensity of index households was identified. Logistic regression analysis identified two main factors associated with a higher proportion of RDT positive household contacts. There was a 41% increased odds of RDT positive household contacts in households where the index case was under 5 years of age [OR = 1.41, 95% confidence intervals (1.15, 1.73)]. For every 500-m increase in distance from the road, there was a 5% increased odds of RDT positive household contacts [OR = 1.05 (1.02, 1.07)], controlling for season. Discussion: Areas of increased report of malaria persist after controlling for distance to the clinic and main road. Clinic-based interventions will miss asymptomatic, non-care seeking infections located farther from the road. RACD may identify additional infections missed at the clinic. [ABSTRACT FROM AUTHOR]

Background: In breast cancer, worse disease characteristics are associated with fewer social resources and black race. However, it is unknown whether social gradients have similar impact across race, and whether behaviors, including tobacco use, may explain a portion of the social gradient. Methods: We modeled relationships between area-level social class, tobacco spending and tumor characteristics, using 50,062 white and black cases diagnosed from 1992-2003 in Maryland, a racially and economically diverse state on the east coast of the United States. Multi-level models estimated the effect of area-level social class and tobacco consumption on tumor grade, size, and stage at diagnosis. Results: Adjusting for race, age and year of diagnosis, higher social class was associated with lower risk for tumors with histological grade 3 or 4 (O.R. 0.96, 95% C.I. 0.94,0.99), those diagnosed at SEER stage 2 or later (O.R. 0.89, 95% C.I. 0.86, 0.91), and tumor size >2 cm (O.R. 0.87, 95% C.I. 0.84, 0.90). Higher tobacco spending was associated with higher risk for higher grade (O.R. 1.01, 1.00, 1.03) and larger tumors (O.R. 1.03, 95% C.I. 1.01, 1.06), but was not statistically significantly related to later stage (O.R. 1.00, 95% C.I. 0.98, 1.02). Social class was less protective for black women, but tobacco effects were not race-specific. Conclusions: Results suggest that in one U.S. geographic area, there is a differential protection from social class for black and white women, supporting use of intersectionality theory in breast cancer disparities investigations. Area-level tobacco consumption may capture cases' direct use and second hand smoke exposure, but also may identify neighborhoods with excess cancer-related behavioral or environmental exposures, beyond those measured by social class. Given the growing global burden of both tobacco addiction and aggressive breast cancer, similar investigations across diverse geographic areas are warranted. [ABSTRACT FROM AUTHOR]

Background: Measles cases may cluster in densely populated urban centers in sub-Saharan Africa as susceptible individuals share spatially dependent risk factors and may cluster among human immunodeficiency virus (HIV)-infected children despite high vaccination coverage. Methods: Children hospitalized with measles at the University Teaching Hospital (UTH) in Lusaka, Zambia were enrolled in the study. The township of residence was recorded on the questionnaire and mapped; SaTScan software was used for cluster detection. A spatial-temporal scan statistic was used to investigate clustering of measles in children hospitalized during an endemic period (1998 to 2002) and during the 2010 measles outbreak in Lusaka, Zambia. Results: Three sequential and spatially contiguous clusters of measles cases were identified during the 2010 outbreak but no clustering among HIV-infected children was identified. In contrast, a space-time cluster among HIV-infected children was identified during the endemic period. This cluster occurred prior to the introduction of intensive measles control efforts and during a period between seasonal peaks in measles incidence. Conclusions: Prediction and early identification of spatial clusters of measles will be critical to achieving measles elimination. HIV infection may contribute to spatial clustering of measles cases in some epidemiological settings. [ABSTRACT FROM AUTHOR]

Background: Spatial variation in patterns of disease outcomes is often explored with techniques such as cluster detection analysis. In other types of investigations, geographically varying individual or community level characteristics are often used as independent predictors in statistical models which also attempt to explain variation in disease outcomes. However, there is a lack of research which combines geographically referenced exploratory analysis with multilevel models. We used a spatial scan statistic approach, in combination with predicted block group-level disease patterns from multilevel models, to examine geographic variation in prostate cancer grade and stage at diagnosis. Results: We examined data from 20928 Maryland men with incident prostate cancer reported to the Maryland Cancer Registry during 1992-1997. Initial cluster detection analyses, prior to adjustment, indicated that there were four statistically significant clusters of high and low rates of each outcome (later stage at diagnosis and higher histologic grade of tumor) for prostate cancer cases in Maryland during 1992-1997. After adjustment for individual case attributes, including age, race, year of diagnosis, patterns of clusters changed for both outcomes. Additional adjustment for Census block group and county-level socioeconomic measures changed the cluster patterns further. Conclusions: These findings provide evidence that, in locations where adjustment changed patterns of clusters, the adjustment factors may be contributing causes of the original clusters. In addition, clusters identified after adjusting for individual and area-level predictors indicate area of unexplained variation, and merit further small-area investigations. [ABSTRACT FROM AUTHOR]