Improving disaggregation models of malaria incidence by ensembling non-linear models of prevalence.

Maps of disease burden are a core tool needed for the control and elimination of malaria. Reliable routine surveillance data of malaria incidence, typically aggregated to administrative units, is becoming more widely available. Disaggregation regression is an important model framework for estimating high resolution risk maps from aggregated data. However, the aggregation of incidence over large, heterogeneous areas means that these data are underpowered for estimating complex, non-linear models. In contrast, prevalence point-surveys are directly linked to local environmental conditions but are not common in many areas of the world. Here, we train multiple non-linear, machine learning models on Plasmodium falciparum prevalence point-surveys. We then ensemble the predictions from these machine learning models with a disaggregation regression model that uses aggregated malaria incidences as response data. We find that using a disaggregation regression model to combine predictions from machine learning models improves model accuracy relative to a baseline model.

Youth in the study of comparative physiology: insights from demography in the wild.

Of all the properties of individual animals of interest to comparative physiologists, age and stage of development are among the most consequential. In a natural population of any species, the survivorship curve is an important determinant of the relative abundances of ages and stages of development. Demography, thus, has significant implications for the study of comparative physiology. When Edward Deevey published his influential summary of survivorship in animal populations in the wild seven decades ago, he emphasized "serious deficiencies" because survivorship curves for natural populations at the time did not include data on the earliest life stages. Such data have accumulated over intervening years. We survey, for the first time, empirical knowledge of early-age survivorship in populations of most major animal groups in a state of nature. Despite wide variation, it is almost universally true that > 50% of newly born or hatched individuals die before the onset of sexual maturity, even in species commonly assumed to exhibit high early-age survivorship. These demographic facts are important considerations for studies in comparative and environmental physiology whether physiologists (i) aim to elucidate function throughout the life cycle, including both early stages and adults, or (ii) focus on adults (in which case early-age survivorship can potentially affect adult characteristics through selection or epigenesis). We establish that Deevey's Type I curve (which applies to species with relatively limited early mortality) has few or no actual analogs in the real, natural world.

Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysis.

BACKGROUND: Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control. METHODS: Using an established set of spatiotemporal Bayesian geostatistical models, we generated geospatial estimates across malaria-endemic African countries of the clinical case incidence and mortality of malaria, incorporating an updated database of parasite rate surveys, insecticide-treated net (ITN) coverage, and effective treatment rates. We established a baseline estimate for the anticipated malaria burden in Africa in the absence of COVID-19-related disruptions, and repeated the analysis for nine hypothetical scenarios in which effective treatment with an antimalarial drug and distribution of ITNs (both through routine channels and mass campaigns) were reduced to varying extents. FINDINGS: We estimated 215·2 (95% uncertainty interval 143·7-311·6) million cases and 386·4 (307·8-497·8) thousand deaths across malaria-endemic African countries in 2020 in our baseline scenario of undisrupted intervention coverage. With greater reductions in access to effective antimalarial drug treatment, our model predicted increasing numbers of cases and deaths: 224·1 (148·7-326·8) million cases and 487·9 (385·3-634·6) thousand deaths with a 25% reduction in antimalarial drug coverage; 233·1 (153·7-342·5) million cases and 597·4 (468·0-784·4) thousand deaths with a 50% reduction; and 242·3 (158·7-358·8) million cases and 715·2 (556·4-947·9) thousand deaths with a 75% reduction. Halting planned 2020 ITN mass distribution campaigns and reducing routine ITN distributions by 25%-75% also increased malaria burden to a total of 230·5 (151·6-343·3) million cases and 411·7 (322·8-545·5) thousand deaths with a 25% reduction; 232·8 (152·3-345·9) million cases and 415·5 (324·3-549·4) thousand deaths with a 50% reduction; and 234·0 (152·9-348·4) million cases and 417·6 (325·5-553·1) thousand deaths with a 75% reduction. When ITN coverage and antimalarial drug coverage were synchronously reduced, malaria burden increased to 240·5 (156·5-358·2) million cases and 520·9 (404·1-691·9) thousand deaths with a 25% reduction; 251·0 (162·2-377·0) million cases and 640·2 (492·0-856·7) thousand deaths with a 50% reduction; and 261·6 (167·7-396·8) million cases and 768·6 (586·1-1038·7) thousand deaths with a 75% reduction. INTERPRETATION: Under pessimistic scenarios, COVID-19-related disruption to malaria control in Africa could almost double malaria mortality in 2020, and potentially lead to even greater increases in subsequent years. To avoid a reversal of two decades of progress against malaria, averting this public health disaster must remain an integrated priority alongside the response to COVID-19. FUNDING: Bill and Melinda Gates Foundation; Channel 7 Telethon Trust, Western Australia.

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.

Timescales of variation in diversity and production of bacterioplankton assemblages in the Lower Mississippi River.

Rivers are characterized by rapid and continuous one-way directional fluxes of flowing, aqueous habitat, chemicals, suspended particles, and resident plankton. Therefore, at any particular location in such systems there is the potential for continuous, and possibly abrupt, changes in diversity and metabolic activities of suspended biota. As microorganisms are the principal catalysts of organic matter degradation and nutrient cycling in rivers, examination of their assemblage dynamics is fundamental to understanding system-level biogeochemical patterns and processes. However, there is little known of the dynamics of microbial assemblage composition or production of large rivers along a time interval gradient. We quantified variation in alpha and beta diversity and production of particle-associated and free-living bacterioplankton assemblages collected at a single site on the Lower Mississippi River (LMR), the final segment of the largest river system in North America. Samples were collected at timescales ranging from days to weeks to months up to a year. For both alpha and beta diversity, there were similar patterns of temporal variation in particle-associated and free-living assemblages. Alpha diversity, while always higher on particles, varied as much at a daily as at a monthly timescale. Beta diversity, in contrast, gradually increased with time interval of sampling, peaking between samples collected 180 days apart, before gradually declining between samples collected up to one year apart. The primary environmental driver of the temporal pattern in beta diversity was temperature, followed by dissolved nitrogen and chlorophyll a concentrations. Particle-associated bacterial production corresponded strongly to temperature, while free-living production was much lower and constant over time. We conclude that particle-associated and free-living bacterioplankton assemblages of the LMR vary in richness, composition, and production at distinct timescales in response to differing sets of environmental factors. This is the first temporal longitudinal study of microbial assemblage structure and dynamics in the LMR.

Patterns of variation in diversity of the Mississippi river microbiome over 1,300 kilometers.

We examined the downriver patterns of variation in taxonomic diversity of the Mississippi River bacterioplankton microbiome along 1,300 river kilometers, or approximately one third the total length of the river. The study section included portions of the Upper, Middle, and Lower Mississippi River, confluences with five tributaries draining distinct sub-basins, river cities, and extended stretches without major inputs to the Mississippi. The composition and proportional abundance of dominant bacterial phyla was distinct for free-living and particle-associated cells, and constant along the entire reach, except for a substantial but transient disturbance near the city of Memphis, Tennessee. At a finer scale of taxonomic resolution (operational taxonomic units, OTUs), however, there were notable patterns in downriver variation in bacterial community alpha diversity (richness within a site) and beta diversity (variation in composition among sites). There was a strong and steady increase downriver in alpha diversity of OTUs on suspended particles, suggesting an increase in particle niche heterogeneity, and/or particle colonization. Relatively large shifts in beta diversity of free-living and particle-associated communities occurred following major tributary confluences and transiently at Memphis, while in long stretches between these points diversity typically varied more gradually. We conclude that the Mississippi River possesses a bacterioplankton microbiome distinct in diversity from other large river microbiomes in the Mississippi River Basin, that at major river confluences or urban point sources its OTU diversity may shift abruptly and substantially, presumably by immigration of distinct external microbiomes, but that where environmental conditions are more stable along the downriver gradient, microbiome diversity tends to vary gradually, presumably by a process of successional change in community composition.

Free-Living and Particle-Associated Bacterioplankton in Large Rivers of the Mississippi River Basin Demonstrate Biogeographic Patterns.

The different drainage basins of large rivers such as the Mississippi River represent interesting systems in which to study patterns in freshwater microbial biogeography. Spatial variability in bacterioplankton communities in six major rivers (the Upper Mississippi, Missouri, Illinois, Ohio, Tennessee, and Arkansas) of the Mississippi River Basin was characterized using Ion Torrent 16S rRNA amplicon sequencing. When all systems were combined, particle-associated (>3 µm) bacterial assemblages were found to be different from free-living bacterioplankton in terms of overall community structure, partly because of differences in the proportional abundance of sequences affiliated with major bacterial lineages (Alphaproteobacteria, Cyanobacteria, and Planctomycetes). Both particle-associated and free-living communities ordinated by river system, a pattern that was apparent even after rare sequences or those affiliated with Cyanobacteria were removed from the analyses. Ordination of samples by river system correlated with environmental characteristics of each river, such as nutrient status and turbidity. Communities in the Upper Mississippi and the Missouri and in the Ohio and the Tennessee, pairs of rivers that join each other, contained similar taxa in terms of presence-absence data but differed in the proportional abundance of major lineages. The most common sequence types detected in particle-associated communities were picocyanobacteria in the Synechococcus/Prochlorococcus/Cyanobium (Syn/Pro) clade, while free-living communities also contained a high proportion of LD12 (SAR11/Pelagibacter)-like Alphaproteobacteria. This research shows that while different tributaries of large river systems such as the Mississippi River harbor distinct bacterioplankton communities, there is also microhabitat variation such as that between free-living and particle-associated assemblages.

Determination of microbial extracellular enzyme activity in waters, soils, and sediments using high throughput microplate assays.

Much of the nutrient cycling and carbon processing in natural environments occurs through the activity of extracellular enzymes released by microorganisms. Thus, measurement of the activity of these extracellular enzymes can give insights into the rates of ecosystem level processes, such as organic matter decomposition or nitrogen and phosphorus mineralization. Assays of extracellular enzyme activity in environmental samples typically involve exposing the samples to artificial colorimetric or fluorometric substrates and tracking the rate of substrate hydrolysis. Here we describe microplate based methods for these procedures that allow the analysis of large numbers of samples within a short time frame. Samples are allowed to react with artificial substrates within 96-well microplates or deep well microplate blocks, and enzyme activity is subsequently determined by absorption or fluorescence of the resulting end product using a typical microplate reader or fluorometer. Such high throughput procedures not only facilitate comparisons between spatially separate sites or ecosystems, but also substantially reduce the cost of such assays by reducing overall reagent volumes needed per sample.