Quantifying Aggregated Uncertainty in Plasmodium falciparum Malaria Prevalence and Populations at Risk via Efficient Space-Time Geostatistical Joint Simulation

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty—the fidelity of predictions at each mapped pixel—but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.     

Quantifying Predation Risk for Refuging Animals: A Case Study with Golden Marmots

Although a variety of behaviors expose animals to some risk of predation, there is no accepted way to compare their relative risk. For animals that retreat to refugia when alarmed by predators, the proportion of time devoted to each out-of-refuge behavior multiplied by the total time required to return to a refuge can be used to compare a behavior's relative predation risk. Total time to return to a refuge is a function of both response time - the time required to respond to an increased risk of predation — and travel time — the time required to flee to a refuge once alarmed. Quantifying these components can illustrate how animals minimize exposure to predators. Golden marmots (Marmota caudata aurea) were a refuging prey species used to examine the utility of this measure and to understand how marmots minimized their risk of exposure to predation. Golden marmots devoted different amounts of time to looking, foraging, self-grooming, and playing. To estimate the behavior-specific time required to return to refugia, the location of different activities was noted and a behavior-specific travel time was calculated. Alarm calls were played back to marmots engaged in different behaviors to determine, in a standardized manner, if there were behavior-specific response times. Marmots appeared to minimize their predation risk by performing most behaviors close to refugia. Results suggest that foraging was the riskiest behavior, largely because marmots foraged far from refugia and spent about 30% of their time foraging. While sample sizes were small, results also suggested that play, a rare adult behavior, exposed animals to predation because of a relatively long response time.     

Estimating the Number of Paediatric Fevers Associated with Malaria Infection Presenting to Africa's Public Health Sector in 2007

Background

As international efforts to increase the coverage of artemisinin-based combination therapy in public health sectors gather pace, concerns have been raised regarding their continued indiscriminate presumptive use for treating all childhood fevers. The availability of rapid-diagnostic tests to support practical and reliable parasitological diagnosis provides an opportunity to improve the rational treatment of febrile children across Africa. However, the cost effectiveness of diagnosis-based treatment polices will depend on the presumed numbers of fevers harbouring infection. Here we compute the number of fevers likely to present to public health facilities in Africa and the estimated number of these fevers likely to be infected with Plasmodium falciparum malaria parasites.

Methods and Findings

We assembled first administrative-unit level data on paediatric fever prevalence, treatment-seeking rates, and child populations. These data were combined in a geographical information system model that also incorporated an adjustment procedure for urban versus rural areas to produce spatially distributed estimates of fever burden amongst African children and the subset likely to present to public sector clinics. A second data assembly was used to estimate plausible ranges for the proportion of paediatric fevers seen at clinics positive for P. falciparum in different endemicity settings. We estimated that, of the 656 million fevers in African 0–4 y olds in 2007, 182 million (28%) were likely to have sought treatment in a public sector clinic of which 78 million (43%) were likely to have been infected with P. falciparum (range 60–103 million).

Conclusions

Spatial estimates of childhood fevers and care-seeking rates can be combined with a relational risk model of infection prevalence in the community to estimate the degree of parasitemia in those fevers reaching public health facilities. This quantification provides an important baseline comparison of malarial and nonmalarial fevers in different endemicity settings that can contribute to ongoing scientific and policy debates about optimum clinical and financial strategies for the introduction of new diagnostics. These models are made publicly available with the publication of this paper. Please see later in the article for the Editors'' Summary     

Risk Factors for Venous Thromboembolism in 1.3 Million Pregnancies: A Nationwide Prospective Cohort

Objective

To quantify risk factors for venous thromboembolism during pregnancy and the puerperal period.

Design

In a nationwide prospective cohort study we followed pregnant and puerperal women in Denmark from 1995 to 2009 for venous thromboembolism. Information on risk factors and confounders was retrieved from national registries. The diagnosis of venous thromboembolism was confirmed through medical charts. We calculated adjusted incidence rates per 10,000 women years and used Poisson regression to estimate effects during pregnancy and the puerperal period.

Results

We studied 1,297,037 pregnancies and related puerperal periods, during which there were 748 venous thromboembolisms. The incidence rate for venous thromboembolism during a pregnancy with and without hospitalization for hyperemesis was 15.2/10,000 yr and 6.3/10,000 yr, respectively, (adjusted rate ratio: 2.5 (95%-confidence interval; 1.4–4.5)). The incidence rate among women with multiple pregnancies was 18.2/10,000 yr and 6.3/10,000 yr in singletons (adjusted rate ratio: 2.8 (1.9–4.2)). Increased risk was found with hospitalization during pregnancy or the puerperal period with incidence rates of 42.1/10.000 and 54.7/10.000, respectively, (rate ratios: 12.2 (8.7–17) and 5.9 (4.0–8.8)). Women hospitalized with infections during pregnancy had incidence rates of 25.9/10,000 yr and 29.3/10,000 yr during pregnancy and the puerperal period, respectively, and of 62.7/10,000 yr if hospitalized with infection in the puerperal period. Puerperal venous thromboembolism was associated with hospitalization for preeclampsia and intrauterine growth restriction/fetal death with incidence rates of 45.8/10,000 yr and 18.3/10,000 yr, respectively (rate ratio: 5.0 (3.1–7.8) and 1.9 (0.9–4.4)). Additionally puerperal venous thromboembolism was associated with obesity, elective and acute caesarean sections and major postpartum bleeding with incidence rates of 25.5/10,000 yr, 23.2/10,000 yr, 34.0/10,000 yr and 20.3/10,000 yr, respectively (rate ratios 1.7 (1.1–2.7), 2.1 (1.4–3.1), 3.0 (2.3–4.0) and 1.4 (1.0–2.1)).

Conclusions

Important risk factors for venous thromboembolism during pregnancy or the puerperal period were hospitalization, infection, hyperemesis, multiple pregnancies, preeclampsia, obesity, caesarean section, major postpartum bleeding, and intrauterine growth restriction or fetal death.     

Estimating the Global Clinical Burden of Plasmodium falciparum Malaria in 2007

Background

The epidemiology of malaria makes surveillance-based methods of estimating its disease burden problematic. Cartographic approaches have provided alternative malaria burden estimates, but there remains widespread misunderstanding about their derivation and fidelity. The aims of this study are to present a new cartographic technique and its application for deriving global clinical burden estimates of Plasmodium falciparum malaria for 2007, and to compare these estimates and their likely precision with those derived under existing surveillance-based approaches.

Methods and Findings

In seven of the 87 countries endemic for P. falciparum malaria, the health reporting infrastructure was deemed sufficiently rigorous for case reports to be used verbatim. In the remaining countries, the mapped extent of unstable and stable P. falciparum malaria transmission was first determined. Estimates of the plausible incidence range of clinical cases were then calculated within the spatial limits of unstable transmission. A modelled relationship between clinical incidence and prevalence was used, together with new maps of P. falciparum malaria endemicity, to estimate incidence in areas of stable transmission, and geostatistical joint simulation was used to quantify uncertainty in these estimates at national, regional, and global scales.Combining these estimates for all areas of transmission risk resulted in 451 million (95% credible interval 349–552 million) clinical cases of P. falciparum malaria in 2007. Almost all of this burden of morbidity occurred in areas of stable transmission. More than half of all estimated P. falciparum clinical cases and associated uncertainty occurred in India, Nigeria, the Democratic Republic of the Congo (DRC), and Myanmar (Burma), where 1.405 billion people are at risk.Recent surveillance-based methods of burden estimation were then reviewed and discrepancies in national estimates explored. When these cartographically derived national estimates were ranked according to their relative uncertainty and replaced by surveillance-based estimates in the least certain half, 98% of the global clinical burden continued to be estimated by cartographic techniques.

Conclusions and Significance

Cartographic approaches to burden estimation provide a globally consistent measure of malaria morbidity of known fidelity, and they represent the only plausible method in those malaria-endemic countries with nonfunctional national surveillance. Unacceptable uncertainty in the clinical burden of malaria in only four countries confounds our ability to evaluate needs and monitor progress toward international targets for malaria control at the global scale. National prevalence surveys in each nation would reduce this uncertainty profoundly. Opportunities for further reducing uncertainty in clinical burden estimates by hybridizing alternative burden estimation procedures are also evaluated. Please see later in the article for the Editors'' Summary     

Mind the Gap: House Structure and the Risk of Malaria in Uganda

Background

Good house construction may reduce the risk of malaria by limiting the entry of mosquito vectors. We assessed how house design may affect mosquito house entry and malaria risk in Uganda.

Methods

100 households were enrolled in each of three sub-counties: Walukuba, Jinja district; Kihihi, Kanungu district; and Nagongera, Tororo district. CDC light trap collections of mosquitoes were done monthly in all homes. All children aged six months to ten years (n = 878) were followed prospectively for a total of 24 months to measure parasite prevalence every three months and malaria incidence. Homes were classified as modern (cement, wood or metal walls; and tiled or metal roof; and closed eaves) or traditional (all other homes).

Results

A total of 113,618 female Anopheles were collected over 6,765 nights. 6,816 routine blood smears were taken of which 1,061 (15.6%) were malaria parasite positive. 2,582 episodes of uncomplicated malaria were diagnosed after 1,569 person years of follow-up, giving an overall incidence of 1.6 episodes per person year at risk. The human biting rate was lower in modern homes than in traditional homes (adjusted incidence rate ratio (IRR) 0.48, 95% confidence interval (CI) 0.37–0.64, p<0.001). The odds of malaria infection were lower in modern homes across all the sub-counties (adjusted odds ratio 0.44, 95%CI 0.30–0.65, p<0.001), while malaria incidence was lower in modern homes in Kihihi (adjusted IRR 0.61, 95%CI 0.40–0.91, p = 0.02) but not in Walukuba or Nagongera.

Conclusions

House design is likely to explain some of the heterogeneity of malaria transmission in Uganda and represents a promising target for future interventions, even in highly endemic areas.     

Malaria: a peek at the var variorum

Geneticists encountering the diversity of the malaria parasite's var gene family for the first time often complain that its complexity is a nightmare. A new article by Barry et al. presents the latest and most systematic attempt to date to decipher the var variorum. This important work, combined with other recent articles on var global variation such as that by Kraemer et al., suggests that only the tip of the var diversity iceberg is currently in view. In this article, we discuss these recent results and provide an overview of current understanding of var diversity.     

Estimating the Sizes of Populations at High Risk for HIV: A Comparison Study

Objectives

Behavioral interventions are effective strategies for HIV/AIDS prevention and control. However, implementation of such strategies relies heavily on the accurate estimation of the high-risk population size. The multiplier method and generalized network scale-up method were recommended to estimate the population size of those at high risk for HIV by UNAIDS/WHO in 2003 and 2010, respectively. This study aims to assess and compare the two methods for estimating the size of populations at high risk for HIV, and to provide practical guidelines and suggestions for implementing the two methods.

Methods

Studies of the multiplier method used to estimate the population prevalence of men who have sex with men in China published between July 1, 2003 and July 1, 2013 were reviewed. The generalized network scale-up method was applied to estimate the population prevalence of men who have sex with men in the urban district of Taiyuan, China.

Results

The median of studies using the multiplier method to estimate the population prevalence of men who have sex with men in China was 4–8 times lower than the national level estimate. Meanwhile, the estimate of the generalized network scale-up method fell within the range of national level estimate.

Conclusions

When high-quality existing data are not readily available, the multiplier method frequently yields underestimated results. We thus suggest that the generalized network scale-up method is preferred when sampling frames for the general population and accurate demographic information are available.     

Malaria Prevalence,Spatial Clustering and Risk Factors in a Low Endemic Area of Eastern Rwanda: A Cross Sectional Study

Background

Rwanda reported significant reductions in malaria burden following scale up of control intervention from 2005 to 2010. This study sought to; measure malaria prevalence, describe spatial malaria clustering and investigate for malaria risk factors among health-centre-presumed malaria cases and their household members in Eastern Rwanda.

Methods

A two-stage health centre and household-based survey was conducted in Ruhuha sector, Eastern Rwanda from April to October 2011. At the health centre, data, including malaria diagnosis and individual level malaria risk factors, was collected. At households of these Index cases, a follow-up survey, including malaria screening for all household members and collecting household level malaria risk factor data, was conducted.

Results

Malaria prevalence among health centre attendees was 22.8%. At the household level, 90 households (out of 520) had at least one malaria-infected member and the overall malaria prevalence for the 2634 household members screened was 5.1%. Among health centre attendees, the age group 5–15 years was significantly associated with an increased malaria risk and a reported ownership of ≥4 bednets was significantly associated with a reduced malaria risk. At the household level, age groups 5–15 and >15 years and being associated with a malaria positive index case were associated with an increased malaria risk, while an observed ownership of ≥4 bednets was associated with a malaria risk-protective effect. Significant spatial malaria clustering among household cases with clusters located close to water- based agro-ecosystems was observed.

Conclusions

Malaria prevalence was significantly higher among health centre attendees and their household members in an area with significant household spatial malaria clustering. Circle surveillance involving passive case finding at health centres and proactive case detection in households can be a powerful tool for identifying household level malaria burden, risk factors and clustering.     

Community-Wide Health Risk Assessment Using Geographically Resolved Demographic Data: A Synthetic Population Approach

Background

Evaluating environmental health risks in communities requires models characterizing geographic and demographic patterns of exposure to multiple stressors. These exposure models can be constructed from multivariable regression analyses using individual-level predictors (microdata), but these microdata are not typically available with sufficient geographic resolution for community risk analyses given privacy concerns.

Methods

We developed synthetic geographically-resolved microdata for a low-income community (New Bedford, Massachusetts) facing multiple environmental stressors. We first applied probabilistic reweighting using simulated annealing to data from the 2006–2010 American Community Survey, combining 9,135 microdata samples from the New Bedford area with census tract-level constraints for individual and household characteristics. We then evaluated the synthetic microdata using goodness-of-fit tests and by examining spatial patterns of microdata fields not used as constraints. As a demonstration, we developed a multivariable regression model predicting smoking behavior as a function of individual-level microdata fields using New Bedford-specific data from the 2006–2010 Behavioral Risk Factor Surveillance System, linking this model with the synthetic microdata to predict demographic and geographic smoking patterns in New Bedford.

Results

Our simulation produced microdata representing all 94,944 individuals living in New Bedford in 2006–2010. Variables in the synthetic population matched the constraints well at the census tract level (e.g., ancestry, gender, age, education, household income) and reproduced the census-derived spatial patterns of non-constraint microdata. Smoking in New Bedford was significantly associated with numerous demographic variables found in the microdata, with estimated tract-level smoking rates varying from 20% (95% CI: 17%, 22%) to 37% (95% CI: 30%, 45%).

Conclusions

We used simulation methods to create geographically-resolved individual-level microdata that can be used in community-wide exposure and risk assessment studies. This approach provides insights regarding community-scale exposure and vulnerability patterns, valuable in settings where policy can be informed by characterization of multi-stressor exposures and health risks at high resolution.     

A Study of Changes in Uterine Leucocytes During Early Pregnancy in the Mouse-vole Interspesific Pregnancies

Mouse and vole embryos were allogeneically and xenogeneically transferred into pseudopregnant CD-1 and immunodeficient （scid） female mice, and we investigated the distribution of uterine leucocytes cells in the implantation sites on days 5,6,and 7 of pregnancy. Macrophages were evenly distributed in the endometrium on days 5 N 7. Neutrophils were rarely seen on days 5 ~ 7, but lymphoeytes were found throughout the endometrium,often in groups associated with glands or the luminal epithelium. The number of uNK cells increased markedly at the mesometrial triangle and the outer decidual area in the CD-1 uteri containing vole embryos; by contrast, scid uteri having vole embryos showed almost the same number as those having mouse embryos. Mast cells were present in large numbers at the myometrium,but rarely in the decidua in all types of pregnant uteri. Cells at the myometrium were more numerous in xenogeneic than in allogeneic transfer. Many mast cells appeared in the inner decidua where xenogeneically transferred vole embryos were dead and aborted. These results suggest the possibility that uterine leucocytes mediate various immunological events in the mouse-vole interspesific pregnancies.     

A Copy Number Variant at the KITLG Locus Likely Confers Risk for Canine Squamous Cell Carcinoma of the Digit

The domestic dog is a robust model for studying the genetics of complex disease susceptibility. The strategies used to develop and propagate modern breeds have resulted in an elevated risk for specific diseases in particular breeds. One example is that of Standard Poodles (STPOs), who have increased risk for squamous cell carcinoma of the digit (SCCD), a locally aggressive cancer that causes lytic bone lesions, sometimes with multiple toe recurrence. However, only STPOs of dark coat color are at high risk; light colored STPOs are almost entirely unaffected, suggesting that interactions between multiple pathways are necessary for oncogenesis. We performed a genome-wide association study (GWAS) on STPOs, comparing 31 SCCD cases to 34 unrelated black STPO controls. The peak SNP on canine chromosome 15 was statistically significant at the genome-wide level (P_raw = 1.60×10⁻⁷; P_genome = 0.0066). Additional mapping resolved the region to the KIT Ligand (KITLG) locus. Comparison of STPO cases to other at-risk breeds narrowed the locus to a 144.9-Kb region. Haplotype mapping among 84 STPO cases identified a minimal region of 28.3 Kb. A copy number variant (CNV) containing predicted enhancer elements was found to be strongly associated with SCCD in STPOs (P = 1.72×10⁻⁸). Light colored STPOs carry the CNV risk alleles at the same frequency as black STPOs, but are not susceptible to SCCD. A GWAS comparing 24 black and 24 light colored STPOs highlighted only the MC1R locus as significantly different between the two datasets, suggesting that a compensatory mutation within the MC1R locus likely protects light colored STPOs from disease. Our findings highlight a role for KITLG in SCCD susceptibility, as well as demonstrate that interactions between the KITLG and MC1R loci are potentially required for SCCD oncogenesis. These findings highlight how studies of breed-limited diseases are useful for disentangling multigene disorders.     

水稻随体染色体的研究

分析了几种野生稻种及栽培稻品种随体染色体的数目,发现不同染色体组型的稻种之间随体染色体数目有一定差异,其中染色体组ＡＡ的有１～２对,随体染色体因品种或样本的来源而异,染色体组ＢＢ的有３对随体染色体,染色体组ＣＣ的有２对随体染色体,染色体组型为ＢＢＣＣ的Ｏｒｙｚａｍｉｎｕｔａ可能有４对随体染色体,而染色体组型为ＣＣＤＤ的Ｏ．ｌａｔｉｆｏｒｉａ则有２对随体染色体。在栽培稻中,不同品种之间随体染色体的数目也存在差异,一般而言,籼稻品种具有两对随体染色体,分别为第１０和第１２染色体,粳稻品种只有一时随体染色体,为第１０染色体。     

Detecting Foci of Malaria Transmission with School Surveys: A Pilot Study in the Gambia

Background

In areas of declining malaria transmission such as in The Gambia, the identification of malaria infected individuals becomes increasingly harder. School surveys may be used to identify foci of malaria transmission in the community.

Methods

The survey was carried out in May–June 2011, before the beginning of the malaria transmission season. Thirty two schools in the Upper River Region of The Gambia were selected with probability proportional to size; in each school approximately 100 children were randomly chosen for inclusion in the study. Each child had a finger prick blood sample collected for the determination of antimalarial antibodies by ELISA, malaria infection by microscopy and PCR, and for haemoglobin measurement. In addition, a simple questionnaire on socio-demographic variables and the use of insecticide-treated bed nets was completed. The cut-off for positivity for antimalarial antibodies was obtained using finite mixture models. The clustered nature of the data was taken into account in the analyses.

Results

A total of 3,277 children were included in the survey. The mean age was 10 years (SD = 2.7) [range 4–21], with males and females evenly distributed. The prevalence of malaria infection as determined by PCR was 13.6% (426/3124) [95% CI = 12.2–16.3] with marked variation between schools (range 3–25%, p<0.001), while the seroprevalence was 7.8% (234/2994) [95%CI = 6.4–9.8] for MSP1₁₉, 11.6% (364/2997) [95%CI = 9.4–14.5] for MSP2, and 20.0% (593/2973) [95% CI = 16.5–23.2) for AMA1. The prevalence of all the three antimalarial antibodies positive was 2.7% (79/2920).

Conclusions

This survey shows that malaria prevalence and seroprevalence before the transmission season were highly heterogeneous.