Trends in treatment-seeking for fever in children under five years old in 151 countries from 1990 to 2020.

Access to medical treatment for fever is essential to prevent morbidity and mortality in individuals and to prevent transmission of communicable febrile illness in communities. Quantification of the rates at which treatment is accessed is critical for health system planning and a prerequisite for disease burden estimates. In this study, national data on the proportion of children under five years old with fever who were taken for medical treatment were collected from all available countries in Africa, Latin America, and Asia (n = 91). We used generalised additive mixed models to estimate 30-year trends in the treatment-seeking rates across the majority of countries in these regions (n = 151). Our results show that the proportions of febrile children brought for medical treatment increased steadily over the last 30 years, with the greatest increases occurring in areas where rates had originally been lowest, which includes Latin America and Caribbean, North Africa and the Middle East (51 and 50% increase, respectively), and Sub-Saharan Africa (23% increase). Overall, the aggregated and population-weighted estimate of children with fever taken for treatment at any type of facility rose from 61% (59-64 95% CI) in 1990 to 71% (69-72 95% CI) in 2020. The overall population-weighted average for fraction of treatment in the public sector was largely unchanged during the study period: 49% (42-58 95% CI) sought care at public facilities in 1990 and 47% (44-52 95% CI) in 2020. Overall, the findings indicate that improvements in access to care have been made where they were most needed, but that despite rapid initial gains, progress can plateau without substantial investment. In 2020 there remained significant gaps in care utilisation that must be factored in when developing control strategies and deriving disease burden estimates.

A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations.

Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four 'dynamical archetypes', each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.

Variation in excess all-cause mortality by age, sex, and province during the first wave of the COVID-19 pandemic in Italy.

Although previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic. By applying the principles of small-area estimation to existing model formulations for excess mortality, this study develops a novel method for assessing excess mortality across small populations and assesses the pattern of COVID excess mortality by province, year, week, age group, and sex in Italy from March through May 2020. We estimate that 53,200 excess deaths occurred across Italy during this time period, compared to just 35,500 deaths where COVID-19 was registered as the underlying cause of death. Out of the total excess mortality burden, 97% of excess deaths occurred among adults over age 60, and 68% of excess deaths were concentrated among adults over age 80. The burden of excess mortality was unevenly distributed across the country, with just three of Italy's 107 provinces accounting for 32% of all excess mortality. This method for estimating excess mortality can be adapted to other countries where COVID-19 diagnostic capacity is still insufficient, and could be incorporated into public health rapid response systems.

Order Matters: The Benefits of Ordinal Fragility Curves for Damage and Loss Estimation.

Probabilistic loss assessments from natural hazards require the quantification of structural vulnerability. Building damage data can be used to estimate fragility curves to obtain realistic descriptions of the relationship between a hazard intensity measure and the probability of exceeding certain damage grades. Fragility curves based on the lognormal cumulative distribution function are popular because of their empirical performance as well as theoretical properties. When we are interested in estimating exceedance probabilities for multiple damage grades, these are usually derived per damage grade via separate probit regressions. However, they can also be obtained simultaneously through an ordinal model which treats the damage grades as ordered and related instead of nominal and distinct. When we use nominal models, a collapse fragility curve is constructed by treating data of "near-collapse" and "no damage" the same: as data of noncollapse. This leads to a loss of information. Using synthetic data as well as real-life data from the 2015 Nepal earthquake, we provide one of the first formal demonstrations of multiple advantages of the ordinal model over the nominal approach. We show that modeling the ordering of damage grades explicitly through an ordinal model leads to higher sensitivity to the data, parsimony and a lower risk of overfitting, noncrossing fragility curves, and lower associated uncertainty.

Global estimation of anti-malarial drug effectiveness for the treatment of uncomplicated Plasmodium falciparum malaria 1991-2019.

BACKGROUND: Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an individual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use; its influence on malaria burden varies through space and time. METHODS: This study uses data from 232 efficacy trials comprised of 86,776 infected individuals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries. RESULTS: The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3-75.8), 70.1% (43.6-76.0) and 71.8% (46.9-76.4) for the 1991-2000, 2006-2010, and 2016-2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9-74.9) for 1991-2000 and 55.5% (27.1-73.4) for 2011-2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials. CONCLUSIONS: This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries' treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.

Efficacy of Selpercatinib in RET Fusion-Positive Non-Small-Cell Lung Cancer.

BACKGROUND: RET fusions are oncogenic drivers in 1 to 2% of non-small-cell lung cancers (NSCLCs). In patients with RET fusion-positive NSCLC, the efficacy and safety of selective RET inhibition are unknown. METHODS: We enrolled patients with advanced RET fusion-positive NSCLC who had previously received platinum-based chemotherapy and those who were previously untreated separately in a phase 1-2 trial of selpercatinib. The primary end point was an objective response (a complete or partial response) as determined by an independent review committee. Secondary end points included the duration of response, progression-free survival, and safety. RESULTS: In the first 105 consecutively enrolled patients with RET fusion-positive NSCLC who had previously received at least platinum-based chemotherapy, the percentage with an objective response was 64% (95% confidence interval [CI], 54 to 73). The median duration of response was 17.5 months (95% CI, 12.0 to could not be evaluated), and 63% of the responses were ongoing at a median follow-up of 12.1 months. Among 39 previously untreated patients, the percentage with an objective response was 85% (95% CI, 70 to 94), and 90% of the responses were ongoing at 6 months. Among 11 patients with measurable central nervous system metastasis at enrollment, the percentage with an objective intracranial response was 91% (95% CI, 59 to 100). The most common adverse events of grade 3 or higher were hypertension (in 14% of the patients), an increased alanine aminotransferase level (in 12%), an increased aspartate aminotransferase level (in 10%), hyponatremia (in 6%), and lymphopenia (in 6%). A total of 12 of 531 patients (2%) discontinued selpercatinib because of a drug-related adverse event. CONCLUSIONS: Selpercatinib had durable efficacy, including intracranial activity, with mainly low-grade toxic effects in patients with RET fusion-positive NSCLC who had previously received platinum-based chemotherapy and those who were previously untreated. (Funded by Loxo Oncology and others; LIBRETTO-001 ClinicalTrials.gov number, NCT03157128.).

Efficacy of Selpercatinib in RET-Altered Thyroid Cancers.

BACKGROUND: RET mutations occur in 70% of medullary thyroid cancers, and RET fusions occur rarely in other thyroid cancers. In patients with RET-altered thyroid cancers, the efficacy and safety of selective RET inhibition are unknown. METHODS: We enrolled patients with RET-mutant medullary thyroid cancer with or without previous vandetanib or cabozantinib treatment, as well as those with previously treated RET fusion-positive thyroid cancer, in a phase 1-2 trial of selpercatinib. The primary end point was an objective response (a complete or partial response), as determined by an independent review committee. Secondary end points included the duration of response, progression-free survival, and safety. RESULTS: In the first 55 consecutively enrolled patients with RET-mutant medullary thyroid cancer who had previously received vandetanib, cabozantinib, or both, the percentage who had a response was 69% (95% confidence interval [CI], 55 to 81), and 1-year progression-free survival was 82% (95% CI, 69 to 90). In 88 patients with RET-mutant medullary thyroid cancer who had not previously received vandetanib or cabozantinib, the percentage who had a response was 73% (95% CI, 62 to 82), and 1-year progression-free survival was 92% (95% CI, 82 to 97). In 19 patients with previously treated RET fusion-positive thyroid cancer, the percentage who had a response was 79% (95% CI, 54 to 94), and 1-year progression-free survival was 64% (95% CI, 37 to 82). The most common adverse events of grade 3 or higher were hypertension (in 21% of the patients), increased alanine aminotransferase level (in 11%), increased aspartate aminotransferase level (in 9%), hyponatremia (in 8%), and diarrhea (in 6%). Of all 531 patients treated, 12 (2%) discontinued selpercatinib owing to drug-related adverse events. CONCLUSIONS: In this phase 1-2 trial, selpercatinib showed durable efficacy with mainly low-grade toxic effects in patients with medullary thyroid cancer with and without previous vandetanib or cabozantinib treatment. (Funded by Loxo Oncology and others; LIBRETTO-001 ClinicalTrials.gov number, NCT03157128.).

Mapping malaria seasonality in Madagascar using health facility data.

BACKGROUND: Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. Identifying location-specific seasonality characteristics is useful for planning interventions. While most existing maps of malaria seasonality use fixed thresholds of rainfall, temperature, and/or vegetation indices to identify suitable transmission months, we construct a statistical modelling framework for characterising the seasonal patterns derived directly from monthly health facility data. METHODS: With data from 2669 of the 3247 health facilities in Madagascar, a spatiotemporal regression model was used to estimate seasonal patterns across the island. In the absence of catchment population estimates or the ability to aggregate to the district level, this focused on the monthly proportions of total annual cases by health facility level. The model was informed by dynamic environmental covariates known to directly influence seasonal malaria trends. To identify operationally relevant characteristics such as the transmission start months and associated uncertainty measures, an algorithm was developed and applied to model realisations. A seasonality index was used to incorporate burden information from household prevalence surveys and summarise 'how seasonal' locations are relative to their surroundings. RESULTS: Positive associations were detected between monthly case proportions and temporally lagged covariates of rainfall and temperature suitability. Consistent with the existing literature, model estimates indicate that while most parts of Madagascar experience peaks in malaria transmission near March-April, the eastern coast experiences an earlier peak around February. Transmission was estimated to start in southeast districts before southwest districts, suggesting that indoor residual spraying should be completed in the same order. In regions where the data suggested conflicting seasonal signals or two transmission seasons, estimates of seasonal features had larger deviations and therefore less certainty. CONCLUSIONS: Monthly health facility data can be used to establish seasonal patterns in malaria burden and augment the information provided by household prevalence surveys. The proposed modelling framework allows for evidence-based and cohesive inferences on location-specific seasonal characteristics. As health surveillance systems continue to improve, it is hoped that more of such data will be available to improve our understanding and planning of intervention strategies.

RET Solvent Front Mutations Mediate Acquired Resistance to Selective RET Inhibition in RET-Driven Malignancies.

INTRODUCTION: Novel rearranged in transfection (RET)-specific tyrosine kinase inhibitors (TKIs) such as selpercatinib (LOXO-292) have shown unprecedented efficacy in tumors positive for RET fusions or mutations, notably RET fusion-positive NSCLC and RET-mutated medullary thyroid cancer (MTC). However, the mechanisms of resistance to these agents have not yet been described. METHODS: Analysis was performed of circulating tumor DNA and tissue in patients with RET fusion-positive NSCLC and RET-mutation positive MTC who developed disease progression after an initial response to selpercatinib. Acquired resistance was modeled preclinically using a CCDC6-RET fusion-positive NSCLC patient-derived xenograft. The inhibitory activity of anti-RET multikinase inhibitors and selective RET TKIs was evaluated in enzyme and cell-based assays. RESULTS: After a dramatic initial response to selpercatinib in a patient with KIF5B-RET NSCLC, analysis of circulating tumor DNA revealed emergence of RET G810R, G810S, and G810C mutations in the RET solvent front before the emergence of clinical resistance. Postmortem biopsy studies reported intratumor and intertumor heterogeneity with distinct disease subclones containing G810S, G810R, and G810C mutations in multiple disease sites indicative of convergent evolution on the G810 residue resulting in a common mechanism of resistance. Acquired mutations in RET G810 were identified in tumor tissue from a second patient with CCDC6-RET fusion-positive NSCLC and in plasma from patients with additional RET fusion-positive NSCLC and RET-mutant MTC progressing on an ongoing phase 1 and 2 trial of selpercatinib. Preclinical studies reported the presence of RET G810R mutations in a CCDC6-RET patient-derived xenograft (from a patient with NSCLC) model of acquired resistance to selpercatinib. Structural modeling predicted that these mutations sterically hinder the binding of selpercatinib, and in vitro assays confirmed loss of activity for both anti-RET multikinase inhibitors and selective RET TKIs. CONCLUSIONS: RET G810 solvent front mutations represent the first described recurrent mechanism of resistance to selective RET inhibition with selpercatinib. Development of potent inhibitor of these mutations and maintaining activity against RET gatekeeper mutations could be an effective strategy to target resistance to selective RET inhibitors.

The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria.

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Furthermore, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD.

Mapping the global endemicity and clinical burden of Plasmodium vivax, 2000-17: a spatial and temporal modelling study.

BACKGROUND: Plasmodium vivax exacts a significant toll on health worldwide, yet few efforts to date have quantified the extent and temporal trends of its global distribution. Given the challenges associated with the proper diagnosis and treatment of P vivax, national malaria programmes-particularly those pursuing malaria elimination strategies-require up to date assessments of P vivax endemicity and disease impact. This study presents the first global maps of P vivax clinical burden from 2000 to 2017. METHODS: In this spatial and temporal modelling study, we adjusted routine malariometric surveillance data for known biases and used socioeconomic indicators to generate time series of the clinical burden of P vivax. These data informed Bayesian geospatial models, which produced fine-scale predictions of P vivax clinical incidence and infection prevalence over time. Within sub-Saharan Africa, where routine surveillance for P vivax is not standard practice, we combined predicted surfaces of Plasmodium falciparum with country-specific ratios of P vivax to P falciparum. These results were combined with surveillance-based outputs outside of Africa to generate global maps. FINDINGS: We present the first high-resolution maps of P vivax burden. These results are combined with those for P falciparum (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The burden of P vivax malaria decreased by 41·6%, from 24·5 million cases (95% uncertainty interval 22·5-27·0) in 2000 to 14·3 million cases (13·7-15·0) in 2017. The Americas had a reduction of 56·8% (47·6-67·0) in total cases since 2000, while South-East Asia recorded declines of 50·5% (50·3-50·6) and the Western Pacific regions recorded declines of 51·3% (48·0-55·4). Europe achieved zero P vivax cases during the study period. Nonetheless, rates of decline have stalled in the past five years for many countries, with particular increases noted in regions affected by political and economic instability. INTERPRETATION: Our study highlights important spatial and temporal patterns in the clinical burden and prevalence of P vivax. Amid substantial progress worldwide, plateauing gains and areas of increased burden signal the potential for challenges that are greater than expected on the road to malaria elimination. These results support global monitoring systems and can inform the optimisation of diagnosis and treatment where P vivax has most impact. FUNDING: Bill & Melinda Gates Foundation and the Wellcome Trust.

Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000-17: a spatial and temporal modelling study.

BACKGROUND: Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden. METHODS: We updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics. FINDINGS: We present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000-17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8-277·7) to 193·9 million (156·6-240·2) and deaths declined from 925 800 (596 900-1 341 100) to 618 700 (368 600-952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017. INTERPRETATION: High-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period. FUNDING: Bill & Melinda Gates Foundation.

malariaAtlas: an R interface to global malariometric data hosted by the Malaria Atlas Project.

BACKGROUND: The Malaria Atlas Project (MAP) has worked to assemble and maintain a global open-access database of spatial malariometric data for over a decade. This data spans various formats and topics, including: geo-located surveys of malaria parasite rate; global administrative boundary shapefiles; and global and regional rasters representing the distribution of malaria and associated illnesses, blood disorders, and intervention coverage. MAP has recently released malariaAtlas, an R package providing a direct interface to MAP's routinely-updated malariometric databases and research outputs. METHODS AND RESULTS: The current paper reviews the functionality available in malariaAtlas and highlights its utility for spatial epidemiological analysis of malaria. malariaAtlas enables users to freely download, visualise and analyse global malariometric data within R. Currently available data types include: malaria parasite rate and vector occurrence point data; subnational administrative boundary shapefiles; and a large suite of rasters covering a diverse range of metrics related to malaria research. malariaAtlas is here used in two mock analyses to illustrate how this data may be incorporated into a standard R workflow for spatial analysis. CONCLUSIONS: malariaAtlas is the first open-access R-interface to malariometric data, providing a new and reproducible means of accessing such data within a freely available and commonly used statistical software environment. In this way, the malariaAtlas package aims to contribute to the environment of data-sharing within the malaria research community.