Longitudinal Surveillance Data Research Articles

Suppression of Aedes aegypti may not affect sympatric Aedes albopictus populations: findings from two years of entomological surveillance in Singapore

Globally, multiple trials have successfully demonstrated the effectiveness of novel tools, such as the sterile and incompatible insect techniques, in suppressing Aedes aegypti populations. However, there is concern that Aedes albopictus, another arbovirus-competent vector, may occupy the niches vacated by Ae. aegypti in areas where these species occur in sympatry. Here we investigate these concerns within the context of a Wolbachia-based Ae. aegypti suppression programme in highly urban Singapore, where general mosquito management is sustained through environmental management. Using nationally representative and longitudinal Aedes surveillance data, we show (1) no consistent association of increase in Ae. albopictus abundance with Ae. aegypti population suppression within Wolbachia-Aedes release sites, and (2) no significant change in the vertical spatial distribution of Ae. albopictus in high-rise residential apartment blocks even after two years of Ae. aegypti suppression. Finally, we report that dengue viruses were less prevalent in field Ae. albopictus than in Ae. aegypti, which is consistent with previous findings that Ae. albopictus is a lesser vector than Ae. aegypti in Singapore. Together, these results indicate that suppression of Ae. aegypti in the community may not be directly associated with any increase of Ae. albopictus population or capacity. Nonetheless, the risk of increase in Ae. albopictus population is anticipated if the reduction in disease transmission leads to less aggressive source reduction efforts and environmental management for mosquito control.

Including transgender populations in mathematical models for HIV treatment and prevention: current barriers and policy implications.

Mathematical models of HIV have been uniquely important in directing and evaluating HIV policy. Transgender and nonbinary people are disproportionately impacted by HIV; however, few mathematical models of HIV transmission have been published that are inclusive of transgender and nonbinary populations. This commentary discusses current structural challenges to developing robust and accurate trans-inclusive models and identifies opportunities for future research and policy, with a focus on examples from the United States. As of April 2024, only seven published mathematical models of HIV transmission include transgender people. Existing models have several notable limitations and biases that limit their utility for informing public health intervention. Notably, no models include transgender men or nonbinary individuals, despite these populations being disproportionately impacted by HIV relative to cisgender populations. In addition, existing mathematical models of HIV transmission do not accurately represent the sexual network of transgender people. Data availability and quality remain a significant barrier to the development of accurate trans-inclusive mathematical models of HIV. Using a community-engaged approach, we developed a modelling framework that addresses the limitations of existing model and to highlight how data availability and quality limit the utility of mathematical models for transgender populations. Modelling is an important tool for HIV prevention planning and a key step towards informing public health interventions, programming and policies for transgender populations. Our modelling framework underscores the importance of accurate trans-inclusive data collection methodologies, since the relevance of these analyses for informing public health decision-making is strongly dependent on the validity of the model parameterization and calibration targets. Adopting gender-inclusive and gender-specific approaches starting from the development and data collection stages of research can provide insights into how interventions, programming and policies can distinguish unique health needs across all gender groups. Moreover, in light of the data structure limitations, designing longitudinal surveillance data systems and probability samples will be critical to fill key research gaps, highlight progress and provide additional rigour to the current evidence. Investments and initiatives like Ending the HIV Epidemic in the United States can be further expanded and are highly needed to prioritize and value transgender populations across funding structures, goals and outcome measures.

Review state-of-the-art of output-based methodological approaches for substantiating freedom from infection.

A wide variety of control and surveillance programmes that are designed and implemented based on country-specific conditions exists for infectious cattle diseases that are not regulated. This heterogeneity renders difficult the comparison of probabilities of freedom from infection estimated from collected surveillance data. The objectives of this review were to outline the methodological and epidemiological considerations for the estimation of probabilities of freedom from infection from surveillance information and review state-of-the-art methods estimating the probabilities of freedom from infection from heterogeneous surveillance data. Substantiating freedom from infection consists in quantifying the evidence of absence from the absence of evidence. The quantification usually consists in estimating the probability of observing no positive test result, in a given sample, assuming that the infection is present at a chosen (low) prevalence, called the design prevalence. The usual surveillance outputs are the sensitivity of surveillance and the probability of freedom from infection. A variety of factors influencing the choice of a method are presented; disease prevalence context, performance of the tests used, risk factors of infection, structure of the surveillance programme and frequency of testing. The existing methods for estimating the probability of freedom from infection are scenario trees, Bayesian belief networks, simulation methods, Bayesian prevalence estimation methods and the STOC free model. Scenario trees analysis is the current reference method for proving freedom from infection and is widely used in countries that claim freedom. Bayesian belief networks and simulation methods are considered extensions of scenario trees. They can be applied to more complex surveillance schemes and represent complex infection dynamics. Bayesian prevalence estimation methods and the STOC free model allow freedom from infection estimation at the herd-level from longitudinal surveillance data, considering risk factor information and the structure of the population. Comparison of surveillance outputs from heterogeneous surveillance programmes for estimating the probability of freedom from infection is a difficult task. This paper is a 'guide towards substantiating freedom from infection' that describes both all assumptions-limitations and available methods that can be applied in different settings.

Influence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year's longitudinal surveillance data: a spatio-temporal modelling study

BackgroundUrbanization greatly affects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases. Schistosomiasis, a common parasitic disease transmitted by the snail Oncomelania hupensis, is mainly found in areas with population aggregations along rivers and lakes where snails live. Previous studies have suggested that factors related to urbanization may influence the infection risk of schistosomiasis, but this association remains unclear. This study aimed to analyse the effect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China.MethodsCounty-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected. The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the National Polar-Orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The geographically and temporally weighted regression model (GTWR) was used to quantify the influence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled. The regression coefficient of urbanization was tested for significance (α = 0.05), and the influence of urbanization on schistosomiasis infection risk was analysed over time and across space based on significant regression coefficients. Variables studied included climate, soil, vegetation, hydrology and topography.ResultsThe mean regression coefficient for urbanization (0.167) is second only to the leached soil area (0.300), which shows that the urbanization is the most important influence factors for schistosomiasis infection risk besides leached soil area. The other important variables are distance to the nearest water source (0.165), mean minimum temperature (0.130), broadleaf forest area (0.105), amount of precipitation (0.073), surface temperature (0.066), soil bulk density (0.037) and grassland area (0.031). The influence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year. During the study period, the significant coefficient of urbanization level increased from − 0.205 to − 0.131.ConclusionsThe influence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous. The urbanization does reduce the risk of schistosomiasis infection to some extend, but the strength of this influence decreases with increasing urbanization. Additionally, the effect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors. This study provides scientific basis for understanding the influence of urbanization on schistosomiasis, and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.

Malaria temporal dynamic clustering for surveillance and intervention planning

BackgroundTargeting interventions where most needed and effective is crucial for public health. Malaria control and elimination strategies increasingly rely on stratification to guide surveillance, to allocate vector control campaigns, and to prioritize access to community-based early diagnosis and treatment (EDT). We developed an original approach of dynamic clustering to improve local discrimination between heterogeneous malaria transmission settings. MethodsWe analysed weekly malaria incidence records obtained from community-based EDT (malaria posts) in Karen/Kayin state, Myanmar. We smoothed longitudinal incidence series over multiple seasons using functional transformation. We regrouped village incidence series into clusters using a dynamic time warping clustering and compared them to the standard, 5-category annual incidence standard stratification. ResultsWe included 1115 villages from 2016 to 2020. We identified eleven P. falciparum and P. vivax incidence clusters which differed by amplitude, trends and seasonality. Specifically the 124 villages classified as “high transmission area” in the standard P. falciparum stratification belonged to the 11 distinct groups when accounting to inter-annual trends and intra-annual variations. Likewise for P. vivax, 399 “high transmission” villages actually corresponded to the 11 distinct dynamics. ConclusionOur temporal dynamic clustering methodology is easy to implement and extracts more information than standard malaria stratification. Our method exploits longitudinal surveillance data to distinguish local dynamics, such as increasing inter-annual trends or seasonal differences, providing key information for decision-making. It is relevant to malaria strategies in other settings and to other diseases, especially when many countries deploy health information systems and collect increasing amounts of health outcome data. FundingThe Bill & Melinda Gates Foundation, The Global Fund against AIDS, Tuberculosis and Malaria (the Regional Artemisinin Initiative) and the Wellcome Trust funded the METF program.

Streptococcus dysgalactiae Bloodstream Infections, Norway, 1999-2021.

Streptococcus dysgalactiae increasingly is recognized as a pathogen of concern for human health. However, longitudinal surveillance data describing temporal trends of S. dysgalactiae are scarce. We retrospectively identified all β-hemolytic streptococcal bloodstream infections reported in Bergen, in western Norway, during 1999-2021. To explore S. dysgalactiae disease burden in a broader context, we mapped the incidence of all microbial species causing bloodstream infections during 2012-2021. We found S. dysgalactiae incidence rates substantially increased during the study period; by 2021, S. dysgalactiae was the fifth most common pathogen causing bloodstream infections in our region. We noted genotypic shifts and found that the rising trend was related in part to the introduction and expansion of the stG62647 emm-type. S. dysgalactiae is among the most common causes of bloodstream infections in western Norway, and increased surveillance and unambiguous species identification are needed to monitor the disease burden attributable to this pathogen.

Linking Lyme disease ecology and epidemiology: reservoir host identity, not richness, determines tick infection and human disease in California

Understanding the community ecology of vector-borne and zoonotic diseases, and how it may shift transmission risk as it responds to environmental change, has become a central focus in disease ecology. Yet, it has been challenging to link the ecology of disease with reported human incidence. Here, we bridge the gap between local-scale community ecology and large-scale disease epidemiology, drawing from a priori knowledge of tick-pathogen-host ecology to model spatially-explicit Lyme disease (LD) risk, and human Lyme disease incidence (LDI) in California. We first use a species distribution modeling approach to model disease risk with variables capturing climate, vegetation, and ecology of key reservoir host species, and host species richness. We then use our modeled disease risk to predict human disease incidence at the zip code level across California. Our results suggest the ecology of key reservoir hosts—particularly dusky-footed woodrats—is central to disease risk posed by ticks, but that host community richness is not strongly associated with tick infection. Predicted disease risk, which is most strongly influenced by the ecology of dusky-footed woodrats, in turn is a strong predictor of human LDI. This relationship holds in the Wildland-Urban Interface, but not in open access public lands, and is stronger in northern California than in the state as a whole. This suggests peridomestic exposure to infected ticks may be more important to LD epidemiology in California than recreational exposure, and underlines the importance of the community ecology of LD in determining human transmission risk throughout this LD endemic region of far western North America. More targeted tick and pathogen surveillance, coupled with studies of human and tick behavior could improve understanding of key risk factors and inform public health interventions. Moreover, longitudinal surveillance data could further improve forecasts of disease risk in response to global environmental change.

Prioritizing Health Care Strategies to Reduce Childhood Mortality

Although child mortality trends have decreased worldwide, deaths among children younger than 5 years of age remain high and disproportionately circumscribed to sub-Saharan Africa and Southern Asia. Tailored and innovative approaches are needed to increase access, coverage, and quality of child health care services to reduce mortality, but an understanding of health system deficiencies that may have the greatest impact on mortality among children younger than 5 years is lacking. To investigate which health care and public health improvements could have prevented the most stillbirths and deaths in children younger than 5 years using data from the Child Health and Mortality Prevention Surveillance (CHAMPS) network. This cross-sectional study used longitudinal, population-based, and mortality surveillance data collected by CHAMPS to understand preventable causes of death. Overall, 3390 eligible deaths across all 7 CHAMPS sites (Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa) between December 9, 2016, and December 31, 2021 (1190 stillbirths, 1340 neonatal deaths, 860 infant and child deaths), were included. Deaths were investigated using minimally invasive tissue sampling (MITS), a postmortem approach using biopsy needles for sampling key organs and fluids. For each death, an expert multidisciplinary panel reviewed case data to determine the plausible pathway and causes of death. If the death was deemed preventable, the panel identified which of 10 predetermined health system gaps could have prevented the death. The health system improvements that could have prevented the most deaths were evaluated for each age group: stillbirths, neonatal deaths (aged <28 days), and infant and child deaths (aged 1 month to <5 years). Of 3390 deaths, 1505 (44.4%) were female and 1880 (55.5%) were male; sex was not recorded for 5 deaths. Of all deaths, 3045 (89.8%) occurred in a healthcare facility and 344 (11.9%) in the community. Overall, 2607 (76.9%) were deemed potentially preventable: 883 of 1190 stillbirths (74.2%), 1010 of 1340 neonatal deaths (75.4%), and 714 of 860 infant and child deaths (83.0%). Recommended measures to prevent deaths were improvements in antenatal and obstetric care (recommended for 588 of 1190 stillbirths [49.4%], 496 of 1340 neonatal deaths [37.0%]), clinical management and quality of care (stillbirths, 280 [23.5%]; neonates, 498 [37.2%]; infants and children, 393 of 860 [45.7%]), health-seeking behavior (infants and children, 237 [27.6%]), and health education (infants and children, 262 [30.5%]). In this cross-sectional study, interventions prioritizing antenatal, intrapartum, and postnatal care could have prevented the most deaths among children younger than 5 years because 75% of deaths among children younger than 5 were stillbirths and neonatal deaths. Measures to reduce mortality in this population should prioritize improving existing systems, such as better access to antenatal care, implementation of standardized clinical protocols, and public education campaigns.

Assessing the associations between Aedes larval indices and dengue risk in Kalutara district, Sri Lanka: a hierarchical time series analysis from 2010 to 2019

BackgroundDengue is a major public health problem in Sri Lanka. Aedes vector surveillance and monitoring of larval indices are routine, long-established public health practices in the country. However, the association between Aedes larval indices and dengue incidence is poorly understood. It is crucial to evaluate lagged effects and threshold values of Aedes larval indices to set pragmatic targets for sustainable vector control interventions.MethodsMonthly Aedes larval indices and dengue cases in all 10 Medical Officer of Health (MOH) divisions in Kalutara district were obtained from 2010 to 2019. Using a novel statistical approach, a distributed lag non-linear model and a two-staged hierarchical meta-analysis, we estimated the overall non-linear and delayed effects of the Premise Index (PI), Breteau Index (BI) and Container Index (CI) on dengue incidence in Kalutara district. A set of MOH division-specific variables were evaluated within the same meta-analytical framework to determine their moderator effects on dengue risk. Using generalized additive models, we assessed the utility of Aedes larval indices in predicting dengue incidence.ResultsWe found that all three larval indices were associated with dengue risk at a lag of 1 to 2 months. The relationship between PI and dengue was homogeneous across MOH divisions, whereas that with BI and CI was heterogeneous. The threshold values of BI, PI and CI associated with dengue risk were 2, 15 and 45, respectively. All three indices showed a low to moderate accuracy in predicting dengue risk in Kalutara district.ConclusionsThis study showed the potential of vector surveillance information in Kalutara district in developing a threshold-based, location-specific early warning system with a lead time of 2 months. The estimated thresholds are nonetheless time-bound and may not be universally applicable. Whenever longitudinal vector surveillance data areavailable, the methodological framework we propose here can be used to estimate location-specific Aedes larval index thresholds in any other dengue-endemic setting.Graphical

Multi-event capture-recapture models estimate the diagnostic performance of serological tests for myxoma and rabbit haemorrhagic disease viruses in the absence of reference samples.

Estimation of the diagnostic performance of serological tests often relies on another test assumed as a reference or on samples of known infection status, yet both are seldom available for emerging pathogens in wildlife. Longitudinal disease serological data can be analysed through multi-event capture-mark-recapture (MECMR) models accounting for the uncertainty in state assignment, allowing us to estimate epidemiological parameters such as incidence and mortality. We hypothesized that by estimating the uncertainty in state assignment, MECMR models estimate the diagnostic performance of serological tests for rabbit haemorrhagic disease virus (RHDV) and myxoma virus (MYXV). We evaluated this hypothesis on longitudinal serological data of three tests of RHDV and one test of MYXV in two populations of the European rabbit (Oryctolagus cuniculus algirus). First, we selected the optimal cut-off threshold for each test using finite mixture models, a reference method not relying on reference tests or samples. Second, we used MECMR models to compare the diagnostic sensitivity (Se) and specificity (Sp) of the three tests for RHDV. Third, we compared the estimates of diagnostic performance by MECMR and finite mixture models across a range of cut-off values. The MECMR models showed that the RHDV test employing GI.2 antigens (Se: 100%) outperformed two tests employing GI.1 antigens (Se: 21.7% ± 8.6% and 8.7% ± 5.9%). At their selected cut-offs (2.0 for RHDV GI.2 and 2.4 for MYXV), the estimates of Se and Sp were concordant between the MECMR and finite mixture models. Over the duration of the study (May 2018 to September 2020), the monthly survival of European rabbits seropositive for MYXV was significantly higher than that of seronegative rabbits (82.7% ± 4.9%versus 61.5% ± 12.7%) at the non-fenced site. We conclude that MECMR models can reliably estimate the diagnostic performance of serological tests for RHDV and MYXV in European rabbits. This conclusion could extend to other diagnostic tests and host-pathogen systems. Longitudinal disease surveillance data analysed through MECMR models allow the validation of diagnostic tests for emerging pathogens in novel host species while simultaneously estimating epidemiological parameters.

The epidemiology of severe malaria at Manhiça District Hospital, Mozambique: a retrospective analysis of 20 years of malaria admissions surveillance data

Most malaria burden estimates rely on modelling infection prevalence to case incidence data, with insufficient attention having been paid to the changing clinical presentation of severe disease and its relationship with changing transmission intensity. We present 20 years of longitudinal surveillance data to contribute to the understanding of the relationship between malaria transmission and the burden and clinical presentation of severe malaria and to inform policy. This retrospective analysis of clinical surveillance hospital data included all children younger than 15 years admitted with malaria to Manhiça District Hospital (MDH), Mozambique, from July 1, 1997, to June 30, 2017. Case fatality ratios (CFRs) were calculated as the number of patients who died having a specific diagnosis or syndrome divided by the total number of patients with known outcome admitted with that diagnosis or syndrome. Over the study period, 32 138 children were admitted to MDH with a malaria diagnosis. Malaria accounted for a large proportion of admissions, ranging from 4083 (76·9%) of 5307 admissions in 2000-01 to 706 (27·5%) of 2568 admissions in 2010-11. Since 2000-02, the absolute and relative number of malaria admissions and deaths presented a decreasing trend. The age pattern of patients with malaria shifted to older ages with a median age of 1·7 years (IQR 0·9-3·0) in 1997-2006 and 2·6 years (IQR 1·3-4·4) in 2006-17, although most malaria deaths (60-88% in 2009-17) still occurred in children younger than 5 years. The clinical presentation of severe malaria changed, with an increase in cerebral malaria and a decrease in severe anaemia and respiratory distress, leading to similar yearly cases for the three syndromes. CFRs for severe malaria fluctuated between 1·1% (2 of 186 in 2014-15) and 7·2% (11 of 152 in 2010-11), varying by severe malaria syndrome (3·3% [70 of 2105] for severe anaemia, 5·1% [191 of 3777] for respiratory distress, and 14·8% [72 of 487] for cerebral malaria). Overall malaria CFRs (1·8% [543 of 30 163]) did not vary by age group. Despite the unprecedented scale up of malaria control tools, malaria still represented around 30-40% of paediatric hospital admissions in 2006-17. The age shift towards older children was not accompanied by an increase in severe malaria or deaths; however, control programmes should consider adapting their high-risk target groups to include older children. Malaria remains a leading cause of disease and health-care system use and the massive unfinished malaria control agenda warrants intensified efforts. Spanish Agency for International Cooperation and Development.

The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus–free program

Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or eradication programs to mitigate BVDV infection and its negative effects. These negative effects of BVDV infection on dairy herds are well documented, but there is much less information about the effects of new introduction of BVDV on dairy herds already participating in a BVDV control program. The objective of our study was to investigate the effect of a new BVDV introduction in BVDV-free herds participating in the Dutch BVDV-free program on herd performance. Longitudinal herd-level surveillance data were combined with herd information data to create 4 unique data sets, including a monthly test-day somatic cell count (SCC) data set, annual calving interval (CIV) and culling risk (CR) data sets, and a quarterly calf mortality rate (CMR) data set. Each database contained 2 types of herds: herds that remained BVDV free during the whole study period (defined as free herds), and herds that lost their BVDV-free status during the study period (defined as breakdown herds). The date of losing the BVDV-free status was defined as breakdown date. To compare breakdown herds with free herds, a random breakdown date was artificially generated for free herds by simple random sampling from the distribution of the breakdown month of the breakdown herds. The SCC and CIV before and after a new introduction of BVDV were compared through linear mixed-effects models with a Gaussian distribution, and the CR and CMR were modeled using a negative binomial distribution in generalized linear mixed-effects models. The explanatory variables for all models included herd type, BVDV status, year, and a random herd effect. Herd size was included as an explanatory variable in the SCC, CIV, and CMR model. Season was included as an explanatory variable in the SCC and CMR model. Results showed that free herds have lower SCC, CR, CMR, and shorter CIV than the breakdown herds. Within the breakdown herds, the new BVDV introduction affected the SCC and CMR. In the year after BVDV introduction, the SCC was higher than that in the year before BVDV introduction, with a factor of 1.011 [2.5th to 97.5th percentile (95% PCTL): 1.002, 1.020]. Compared with the year before BVDV breakdown, the CMR in the year of breakdown and the year after breakdown was higher, with factors of 1.170 (95% PCTL: 1.120; 1.218) and 1.096 (95% PCTL: 1.048; 1.153), respectively. This study reveals that a new introduction of BVDV had a negative but on average relatively small effect on herd performance in herds participating in a BVDV control program.

#63: Antibodies to Peptides Representing Plasmodium falciparum Circumsporozoite Protein Reflect Acquisition of Naturally Acquired Immunity in Malian Adults and Children

Abstract Background An effective vaccine against Plasmodium falciparum, the most common and deadly cause of malaria, is a global priority. Circumsporozoite protein (CSP) is a major P. falciparum vaccine target. Previously recognized CSP epitopes include the immunodominant NANP repeat region, the conserved junction between Region 1 (R1) and the NANP repeats, and the polymorphic Th2R and Th3R in the C-terminus. RTS,S, the most advanced vaccine to date, contains 19 NANP repeats and the C-terminus from the 3D7 parasite clone. CSP-specific monoclonal antibodies to the R1-NANP junctional region showed potent neutralizing activity in vitro and in vivo and are therefore under development for immunoprophylaxis. However, little is known about naturally acquired humoral immunity to precise and diverse epitopes along the CSP sequence, especially in the R1-NANP junctional region. Our goal was to use novel high-throughput tools to examine immunity to diverse CSP epitopes. Methods We probed sera from 10 adults and 10 children from Bandiagara, Mali, a region with intense, seasonal malaria transmission, on a diversity-reflecting peptide microarray. This microarray included 73 CSP variants from reference genomes and field-derived genomic data represented as 16 amino acid (aa) peptides with 12 aa overlap. We used a sliding window-based average smoothing procedure to determine log2 transformed signal intensities (SI) at each aa position. SI and serorecognition, defined as SI &amp;gt;2.5 standard deviations above the mean SI of malaria-naïve controls, were compared. We used the Wilcoxon rank-sum test for comparisons between adults and children and the Wilcoxon signed-rank test for matched comparisons of children over the malaria season, with the Benjamini-Hochberg procedure to control the false discovery rate. Results Adult sera recognized more variants than children at 313 of the 401 positions along CSP, including areas of the R1-NANP junctional region, the NANP repeat region, and the C-terminal Th2R and Th3R epitopes. Adults had higher SI than children to variants in known epitopes, including the R1-NANP junctional region and NANP, but not to a large portion of the 3D7 sequence of Th2R. Across the malaria season, children did not recognize significantly more variants at any one position. However, children had higher SI mid-season when compared with pre-season at a few small epitopes in the R1-NANP junctional region and Th2R. No significant differences existed between SI at any position when comparing post- to mid- or pre-season. Conclusions We identified precise CSP epitopes where serologic responses differed between adults and children and in children over a malaria season in Bandiagara. Adults showed responses to more variants and higher antibody responses at the R1-NANP junctional region and the NANP repeat region, but not to the 3D7 variant sequence in the Th2R epitope, which is included in RTS,S. Children acquired some short-lived immunity to the R1-NANP junctional region and a Th2R epitope during the season but not the NANP repeat region. Our limitations included a small sample size. Next steps include differentiation of immunodominant from protective responses in a larger study with longitudinal infection surveillance data.

Incidence of hospital-acquired influenza in adults: A prospective surveillance study from 2004 to 2017 in a French tertiary care hospital

Hospital-acquired influenza potentially leads to significant morbidity and mortality in already vulnerable patients, but its overall burden is not fully understood. We undertook this study to estimate the incidence and trends of hospital-acquired laboratory-confirmed influenza among adults, and to compare clinical characteristics between hospital-acquired and community-acquired influenza cases. This was a prospective surveillance study over 11 years of adults with influenza-like-illness (ILI) hospitalized in surgery, medicine and geriatric wards in a tertiary acute-care hospital in Lyon, France. Nasal swabs were systematically collected from those with ILI and tested for influenza by reverse transcriptase-polymerase chain reaction at the national influenza reference laboratory (Lyon, France). Influenza was laboratory confirmed at a rate of 1 in 13 patients who developed ILI during their hospitalization. Having an underlying disease was an important characteristic of hospital-acquired ILI cases. Cardiovascular disease was the most frequent underlying condition in both influenza-positive and influenza-negative patients. Complications were more frequent for influenza-positive than influenza-negative patients. The influenza incidence rate was highest in the geriatric ward and increased over the study period. Hospital-acquired influenza poses a significant risk to already vulnerable patients. Longitudinal surveillance data are essential to support better recognition and monitoring of viral infections in hospitals.

Spatiotemporal distribution and socioeconomic disparities of dengue, chikungunya and Zika in two Latin American cities from 2007 to 2017.

To assess the presence, pattern and magnitude of socioeconomic inequalities on dengue, chikungunya and Zika in Latin America, accounting for their spatiotemporal distribution. Using longitudinal surveillance data (reported arboviruses) from Fortaleza, Brazil and Medellin, Colombia (2007-2017), we fit Bayesian hierarchical models with structured random effects to estimate: (i) spatiotemporally adjusted incidence rates; (ii) Relative Concentration Index and Absolute Concentration Index of inequality; (iii) temporal trends in RCIs; and (iv) socioeconomic-specific estimates of disease distribution. The spatial analysis was conducted at the neighbourhood level (urban settings). The socioeconomic measures were the median monthly household income (MMHI) for Brazil and the Socio-Economic Strata index (SES) in Colombia. There were 281426 notified arboviral cases in Fortaleza and 40887 in Medellin. We observed greater concentration of dengue among residents of low socioeconomic neighbourhoods in both cities: Relative Concentration Index=-0.12 (95% CI=-0.13, -0.10) in Fortaleza and Relative Concentration Index=-0.04 (95% CI=-0.05, -0.03) in Medellin. The magnitude of inequalities varied over time across sites and was larger during outbreaks. We identified a non-monotonic association between disease rates and socioeconomic measures, especially for chikungunya, that changed over time. The Relative Concentration Index and Absolute Concentration Index showed few if any inequalities for Zika. The socioeconomic-specific model showed increased disease rates at MMHI below US$400 in Brazil and at SES-index below level four, in Colombia. We provide robust quantitative estimates of socioeconomic inequalities in arboviruses for two Latin American cities. Our findings could inform policymaking by identifying spatial hotspots for arboviruses and targeting strategies to decrease disparities at the local level.

Trends in the prevalence and incidence of orphanhood in children and adolescents

BackgroundIn South Africa, large increases in early adult mortality during the 1990s and early 2000s have reversed since public HIV treatment rollout in 2004. In a rural population in KwaZulu-Natal, we investigate trends in parental mortality and orphanhood from 2000–2014.MethodsUsing longitudinal demographic surveillance data for a population of approximately 90,000, we calculated annual incidence and prevalence of maternal, paternal and double orphanhood in children and adolescents (<20 years) and, overall and cause-specific mortality of parents by age.ResultsThe proportion of children and adolescents (<20 years) for whom one or both parents had died rose from 26% in 2000 to peak at 36% in 2010, followed by a decline to 32% in 2014. The burden of orphanhood remains high especially in the oldest age group: in 2014, 53% of adolescents 15–19 years had experienced the death of one or both parents. In all age groups and years, paternal orphan prevalence was three-five times higher than maternal orphan prevalence. Maternal and paternal orphan incidence peaked in 2005 at 17 and 27 per 1,000 person years respectively (<20 years) before declining by half through 2014. The leading cause of parental death throughout the period, HIV/AIDS and TB cause-specific mortality rates declined substantially in mothers and fathers from 2007 and 2009 respectively.ConclusionsThe survival of parents with children and adolescents <20 years has improved in tandem with earlier initiation and higher coverage of HIV treatment. However, comparatively high levels of parental deaths persist in this rural population in KwaZulu-Natal, particularly among fathers. Community-level surveillance to estimate levels of orphanhood remains important for monitoring and evaluation of targeted state welfare support for orphans and their guardians.

Increased mosquito abundance and species richness in Connecticut, United States 2001\u20132019

Historical declines in multiple insect taxa have been documented across the globe in relation to landscape-level changes in land use and climate. However, declines have either not been universally observed in all regions or examined for all species. Because mosquitoes are insects of public health importance, we analyzed a longitudinal mosquito surveillance data set from Connecticut (CT), United States (U.S.) from 2001 to 2019 to identify changes in mosquito community composition over time. We first analyzed annual site-level collections and metrics of mosquito community composition with generalized linear/additive mixed effects models; we also examined annual species-level collections using the same tools. We then examined correlations between statewide collections and weather variables as well as site-level collections and land cover classifications. We found evidence that the average trap night collection of mosquitoes has increased by ~ 60% and statewide species richness has increased by ~ 10% since 2001. Total species richness was highest in the southern portion of CT, likely due to the northward range expansion of multiple species within the Aedes, Anopheles, Culex, and Psorophora genera. How the expansion of mosquito populations in the northeast U.S. will alter mosquito-borne pathogen transmission in the region will require further investigation.

Open-defecation and Attainment of SDG Six - Evidence from Kintampo Health and Demographic Surveillance System in Ghana

BackgroundThe Sustainable Development Goal (SDG) six partly targets at ending open defecation (OD) by 2030. It is essential to assess progress towards this target in sub-Saharan Africa (SSA) where the sanitation target of the Millennium Development Goal (MDG) was largely not achieved. About 215 million people are involved in OD in SSA. In Ghana, it is estimated that three out of five Ghanaians practice OD. This study examined whether the OD free target is achievable by 2030.MethodThis study used longitudinal health and demographic surveillance data from two districts in Kintampo. Data were collected from household heads or their representatives over a 12-year period. In an exploratory analysis, the correlation between total number of households, year, and total number of OD households was obtained. The average percentage yearly increase in OD was computed and used to project the percentage of OD for the years 2020, 2025 and 2030. In addition, geo-spatial technology was used to visualize variability in OD across the twelve sub-Districts. ResultsThe results showed that the OD free target is not achievable in 2030 or even after if the current trend continues. In 2016, more than two out of five households defecate openly. In six out of the 12 sub-Districts, more than half of the households openly defecated. Four out of these six sub-Districts were in the Kintampo North Municipality.ConclusionThe 2030 OD free target is not achievable in the Kintampo districts of Ghana.

Potential Gains in Reproductive-Aged Life Expectancy if Maternal Mortality were Eradicated from the Kintampo Districts of Central Ghana

Background: Almost 99 percent of pregnancy or childbirth-related complications globally is estimated to occur in developing regions. Yet, little is known about the demographic impact of maternal causes of death (COD) in low-and middle-income countries. Assuming that critical interventions were implemented such that maternal mortality is eradicated as a major cause of death, how would it translate to improved longevity for reproductive-aged women in the Kintampo districts of Ghana?Methods: The study used longitudinal health and demographic surveillance data from the Kintampo districts to assess the effect of hypothetically eradicating maternal COD on reproductive-aged life expectancy by applying multiple decrement and associated single decrement life table techniques.Results: According to the results, on the average, women would have lived an additional 4.4 years in their reproductive age if maternal mortality were eradicated as a cause of death, rising from an average of 28.7 years lived during the 2005-2014 period to 33.1 years assuming that maternal mortality was eradicated. The age patterns of maternal-related mortality and all-cause mortality depict that the maternal-related mortality is different from the all-cause mortality for women of reproductive age.Conclusion: This observation suggests that other COD are competing with maternal mortality among the WRA in the study area and during the study period.

Potential gains in reproductive-aged life expectancy if maternal mortality were eradicated from the Kintampo districts of Central Ghana

BackgroundAlmost 99% of pregnancy or childbirth-related complications globally is estimated to occur in developing regions. Yet, little is known about the demographic impact of maternal causes of death (COD) in low-and middle-income countries. Assuming that critical interventions were implemented such that maternal mortality is eradicated as a major cause of death, how would it translate to improved longevity for reproductive-aged women in the Kintampo districts of Ghana?MethodsThe study used longitudinal health and demographic surveillance data from the Kintampo districts to assess the effect of hypothetically eradicating maternal COD on reproductive-aged life expectancy by applying multiple decrement and associated single decrement life table techniques.ResultsAccording to the results, on the average, women would have lived an additional 4.4 years in their reproductive age if maternal mortality were eradicated as a cause of death, rising from an average of 28.7 years lived during the 2005-2014 period to 33.1 years assuming that maternal mortality was eradicated. The age patterns of maternal-related mortality and all-cause mortality depict that the maternal-related mortality is different from the all-cause mortality for women of reproductive age.ConclusionThis observation suggests that other COD are competing with maternal mortality among the WRA in the study area and during the study period.