coiaf: Directly estimating complexity of infection with allele frequencies.

In malaria, individuals are often infected with different parasite strains. The complexity of infection (COI) is defined as the number of genetically distinct parasite strains in an individual. Changes in the mean COI in a population have been shown to be informative of changes in transmission intensity with a number of probabilistic likelihood and Bayesian models now developed to estimate the COI. However, rapid, direct measures based on heterozygosity or FwS do not properly represent the COI. In this work, we present two new methods that use easily calculated measures to directly estimate the COI from allele frequency data. Using a simulation framework, we show that our methods are computationally efficient and comparably accurate to current approaches in the literature. Through a sensitivity analysis, we characterize how the distribution of parasite densities, the assumed sequencing depth, and the number of sampled loci impact the bias and accuracy of our two methods. Using our developed methods, we further estimate the COI globally from Plasmodium falciparum sequencing data and compare the results against the literature. We show significant differences in the estimated COI globally between continents and a weak relationship between malaria prevalence and COI.

Reassessing Reported Deaths and Estimated Infection Attack Rate during the First 6 Months of the COVID-19 Epidemic, Delhi, India.

India reported >10 million coronavirus disease (COVID-19) cases and 149,000 deaths in 2020. To reassess reported deaths and estimate incidence rates during the first 6 months of the epidemic, we used a severe acute respiratory syndrome coronavirus 2 transmission model fit to data from 3 serosurveys in Delhi and time-series documentation of reported deaths. We estimated 48.7% (95% credible interval 22.1%-76.8%) cumulative infection in the population through the end of September 2020. Using an age-adjusted overall infection fatality ratio based on age-specific estimates from mostly high-income countries, we estimated that just 15.0% (95% credible interval 9.3%-34.0%) of COVID-19 deaths had been reported, indicating either substantial underreporting or lower age-specific infection-fatality ratios in India than in high-income countries. Despite the estimated high attack rate, additional epidemic waves occurred in late 2020 and April-May 2021. Future dynamics will depend on the duration of natural and vaccine-induced immunity and their effectiveness against new variants.

Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling.

Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.

Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia, in the context of vaccination rollout.

BACKGROUND: As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. METHODS: We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine rollout. RESULTS: C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. CONCLUSIONS: Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.

Describing the current status of Plasmodium falciparum population structure and drug resistance within mainland Tanzania using molecular inversion probes.

High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programmes, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania countrywide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, approximately separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from nearby districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts (including two infections carrying pfk13-R561H), and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared.

Spatially clustered count data provide more efficient search strategies in invasion biology and disease control.

Geographic profiling, a mathematical model originally developed in criminology, is increasingly being used in ecology and epidemiology. Geographic profiling boasts a wide range of applications, such as finding source populations of invasive species or breeding sites of vectors of infectious disease. The model provides a cost-effective approach for prioritizing search strategies for source locations and does so via simple data in the form of the positions of each observation, such as individual sightings of invasive species or cases of a disease. In doing so, however, classic geographic profiling approaches fail to make the distinction between those areas containing observed absences and those areas where no data were recorded. Absence data are generated via spatial sampling protocols but are often discarded during the inference process. Here we construct a geographic profiling model that resolves these issues by making inferences via count data, analyzing a set of discrete sentinel locations at which the number of encounters has been recorded. Crucially, in our model this number can be zero. We verify the ability of this new model to estimate source locations and other parameters of practical interest via a Bayesian power analysis. We also measure model performance via real-world data in which the model infers breeding locations of mosquitoes in bromeliads in Miami-Dade County, Florida, USA. In both cases, our novel model produces more efficient search strategies by shifting focus from those areas containing observed absences to those with no data, an improvement over existing models that treat these areas equally. Our model makes important improvements upon classic geographic profiling methods, which will significantly enhance real-world efforts to develop conservation management plans and targeted interventions.

Response to COVID-19 in South Korea and implications for lifting stringent interventions.

BACKGROUND: After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their "test, trace, isolate" strategy. However, it is important to understand the epidemiological peculiarities of South Korea's outbreak and characterise their response before attempting to emulate these measures elsewhere. METHODS: We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. RESULTS: We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent "lockdown" measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. CONCLUSIONS: Whilst early adoption of testing and contact tracing is likely to be important for South Korea's successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.

The changing landscape of Plasmodium falciparum drug resistance in the Democratic Republic of Congo.

BACKGROUND: Drug resistant malaria is a growing concern in the Democratic Republic of the Congo (DRC), where previous studies indicate that parasites resistant to sulfadoxine/pyrimethamine or chloroquine are spatially clustered. This study explores longitudinal changes in spatial patterns to understand how resistant malaria may be spreading within the DRC, using samples from nation-wide population-representative surveys. METHODS: We selected 552 children with PCR-detectable Plasmodium falciparum infection and identified known variants in the pfdhps and pfcrt genes associated with resistance. We compared the proportion of mutant parasites in 2013 to those previously reported from adults in 2007, and identified risk factors for carrying a resistant allele using multivariate mixed-effects modeling. Finally, we fit a spatial-temporal model to the observed data, providing smooth allele frequency estimates over space and time. RESULTS: The proportion of co-occurring pfdhps K540E/A581G mutations increased by 16% between 2007 and 2013. The spatial-temporal model suggests that the spatial range of the pfdhps double mutants expanded over time, while the prevalence and range of pfcrt mutations remained steady. CONCLUSIONS: This study uses population-representative samples to describe the changing landscape of SP resistance within the DRC, and the persistence of chloroquine resistance. Vigilant molecular surveillance is critical for controlling the spread of resistance.

Drug-Resistance and Population Structure of Plasmodium falciparum Across the Democratic Republic of Congo Using High-Throughput Molecular Inversion Probes.

A better understanding of the drivers of the spread of malaria parasites and drug resistance across space and time is needed. These drivers can be elucidated using genetic tools. Here, a novel molecular inversion probe (MIP) panel targeting all major drug-resistance mutations and a set of microsatellites was used to genotype Plasmodium falciparum infections of 552 children from the 2013-2014 Demographic and Health Survey conducted in the Democratic Republic of the Congo (DRC). Microsatellite-based analysis of population structure suggests that parasites within the DRC form a homogeneous population. In contrast, sulfadoxine-resistance markers in dihydropteroate synthase show marked spatial structure with ongoing spread of double and triple mutants compared with 2007. These findings suggest that parasites in the DRC remain panmictic despite rapidly spreading antimalarial-resistance mutations. Moreover, highly multiplexed targeted sequencing using MIPs emerges as a cost-effective method for elucidating pathogen genetics in complex infections in large cohorts.

Modelling population-level impact to inform target product profiles for childhood malaria vaccines.

BACKGROUND: The RTS,S/AS01 vaccine for Plasmodium falciparum malaria demonstrated moderate efficacy in 5-17-month-old children in phase 3 trials, and from 2018, the vaccine will be evaluated through a large-scale pilot implementation program. Work is ongoing to optimise this vaccine, with higher efficacy for a different schedule demonstrated in a phase 2a challenge study. The objective of our study was to investigate the population-level impact of a modified RTS,S/AS01 schedule and dose amount in order to inform the target product profile for a second-generation malaria vaccine. METHODS: We used a mathematical modelling approach as the basis for our study. We simulated the changing anti-circumsporozoite antibody titre following vaccination and related the titre to vaccine efficacy. We then implemented this efficacy profile within an individual-based model of malaria transmission. We compared initial efficacy, duration and dose timing, and evaluated the potential public health impact of a modified vaccine in children aged 5-17 months, measuring clinical cases averted in children younger than 5 years. RESULTS: In the first decade of delivery, initial efficacy was associated with a higher reduction in childhood clinical cases compared to vaccine duration. This effect was more pronounced in high transmission settings and was due to the efficacy benefit occurring in younger ages where disease burden is highest. However, the low initial efficacy and long duration schedule averted more cases across all age cohorts if a longer time horizon was considered. We observed an age-shifting effect due to the changing immunological profile in higher transmission settings, in scenarios where initial efficacy was higher, and the fourth dose administered earlier. CONCLUSIONS: Our findings indicate that, for an imperfect childhood malaria vaccine with suboptimal efficacy, it may be advantageous to prioritise initial efficacy over duration. We predict that a modified vaccine could outperform the current RTS,S/AS01, although fourth dose timing will affect the age group that derives the greatest benefit. Further, the outcome measure and timeframe over which a vaccine is assessed are important when prioritising vaccine elements. This study provides insight into the most important characteristics of a malaria vaccine for at-risk groups and shows how distinct vaccine properties translate to public health outcomes. These findings may be used to prioritise target product profile elements for second-generation childhood malaria vaccines.

Correction to: Mapping malaria by combining parasite genomic and epidemiologic data.

The original article [1] contained an error in the presentation of Figure 1; this error has now been rectified and Figure 1 is now presented correctly.

Mapping malaria by combining parasite genomic and epidemiologic data.

BACKGROUND: Recent global progress in scaling up malaria control interventions has revived the goal of complete elimination in many countries. Decreasing transmission intensity generally leads to increasingly patchy spatial patterns of malaria transmission in elimination settings, with control programs having to accurately identify remaining foci in order to efficiently target interventions. FINDINGS: The role of connectivity between different pockets of local transmission is of increasing importance as programs near elimination since humans are able to transfer parasites beyond the limits of mosquito dispersal, thus re-introducing parasites to previously malaria-free regions. Here, we discuss recent advances in the quantification of spatial epidemiology of malaria, particularly Plasmodium falciparum, in the context of transmission reduction interventions. Further, we highlight the challenges and promising directions for the development of integrated mapping, modeling, and genomic approaches that leverage disparate datasets to measure both connectivity and transmission. CONCLUSION: A more comprehensive understanding of the spatial transmission of malaria can be gained using a combination of parasite genetics and epidemiological modeling and mapping. However, additional molecular and quantitative methods are necessary to answer these public health-related questions.

Plasmodium falciparum genetic variation of var2csa in the Democratic Republic of the Congo.

BACKGROUND: The Democratic Republic of the Congo (DRC) bears a high burden of malaria, which is exacerbated in pregnant women. The VAR2CSA protein plays a crucial role in pregnancy-associated malaria (PAM), and hence quantifying diversity at the var2csa locus in the DRC is important in understanding the basic epidemiology of PAM, and in developing a robust vaccine against PAM. METHODS: Samples were taken from the 2013-14 Demographic and Health Survey conducted in the DRC, focusing on children under 5 years of age. A short subregion of the var2csa gene was sequenced in 115 spatial clusters, giving country-wide estimates of sequence polymorphism and spatial population structure. RESULTS: Results indicate that var2csa is highly polymorphic, and that diversity is being maintained through balancing selection, however, there is no clear signal of phylogenetic or geographic structure to this diversity. Linear modelling demonstrates that the number of var2csa variants in a cluster correlates directly with cluster prevalence, but not with other epidemiological factors such as urbanicity. CONCLUSIONS: Results suggest that the DRC fits within the global pattern of high var2csa diversity and little genetic differentiation between regions. A broad multivalent VAR2CSA vaccine candidate could benefit from targeting stable regions and common variants to address the substantial genetic diversity.

Population sensitivity of acute flaccid paralysis and environmental surveillance for serotype 1 poliovirus in Pakistan: an observational study.

BACKGROUND: To support poliomyelitis eradication in Pakistan, environmental surveillance (ES) of wastewater has been expanded alongside surveillance for acute flaccid paralysis (AFP). ES is a relatively new method of surveillance, and the population sensitivity of detecting poliovirus within endemic settings requires estimation. METHODS: Data for wild serotype 1 poliovirus from AFP and ES from January 2011 to September 2015 from 14 districts in Pakistan were analysed using a multi-state model framework. This framework was used to estimate the sensitivity of poliovirus detection from each surveillance source and parameters such as the duration of infection within a community. RESULTS: The location and timing of poliomyelitis cases showed spatial and temporal variability. The sensitivity of AFP surveillance to detect serotype 1 poliovirus infection in a district and its neighbours per month was on average 30.0% (95% CI 24.8-35.8) and increased with the incidence of poliomyelitis cases. The average population sensitivity of a single environmental sample was 59.4% (95% CI 55.4-63.0), with significant variation in site-specific estimates (median varied from 33.3-79.2%). The combined population sensitivity of environmental and AFP surveillance in a given month was on average 98.1% (95% CI 97.2-98.7), assuming four samples per month for each site. CONCLUSIONS: ES can be a highly sensitive supplement to AFP surveillance in areas with converging sewage systems. As ES for poliovirus is expanded, it will be important to identify factors associated with variation in site sensitivity, leading to improved site selection and surveillance system performance.

Pfhrp2-Deleted Plasmodium falciparum Parasites in the Democratic Republic of the Congo: A National Cross-sectional Survey.

Background: Rapid diagnostic tests (RDTs) account for more than two-thirds of malaria diagnoses in Africa. Deletions of the Plasmodium falciparum hrp2 (pfhrp2) gene cause false-negative RDT results and have never been investigated on a national level. Spread of pfhrp2-deleted P. falciparum mutants, resistant to detection by HRP2-based RDTs, would represent a serious threat to malaria elimination efforts. Methods: Using a nationally representative cross-sectional study of 7,137 children under five years of age from the Democratic Republic of Congo (DRC), we tested 783 subjects with RDT-/PCR+ results using PCR assays to detect and confirm deletions of the pfhrp2 gene. Spatial and population genetic analyses were employed to examine the distribution and evolution of these parasites. Results: We identified 149 pfhrp2-deleted parasites, representing 6.4% of all P. falciparum infections country-wide (95% confidence interval 5.1-8.0%). Bayesian spatial analyses identified statistically significant clustering of pfhrp2 deletions near Kinshasa and Kivu. Population genetic analysis revealed significant genetic differentiation between wild-type and pfhrp2-deleted parasite populations (GST = .046, p ≤ .00001). Conclusions: Pfhrp2-deleted P. falciparum is a common cause of RDT-/PCR+ malaria among asymptomatic children in the DRC and appears to be clustered within select communities. Surveillance for these deletions is needed, and alternatives to HRP2-specific RDTs may be necessary.

Public health impact and cost-effectiveness of the RTS,S/AS01 malaria vaccine: a systematic comparison of predictions from four mathematical models.

BACKGROUND: The phase 3 trial of the RTS,S/AS01 malaria vaccine candidate showed modest efficacy of the vaccine against Plasmodium falciparum malaria, but was not powered to assess mortality endpoints. Impact projections and cost-effectiveness estimates for longer timeframes than the trial follow-up and across a range of settings are needed to inform policy recommendations. We aimed to assess the public health impact and cost-effectiveness of routine use of the RTS,S/AS01 vaccine in African settings. METHODS: We compared four malaria transmission models and their predictions to assess vaccine cost-effectiveness and impact. We used trial data for follow-up of 32 months or longer to parameterise vaccine protection in the group aged 5-17 months. Estimates of cases, deaths, and disability-adjusted life-years (DALYs) averted were calculated over a 15 year time horizon for a range of levels of Plasmodium falciparum parasite prevalence in 2-10 year olds (PfPR2-10; range 3-65%). We considered two vaccine schedules: three doses at ages 6, 7·5, and 9 months (three-dose schedule, 90% coverage) and including a fourth dose at age 27 months (four-dose schedule, 72% coverage). We estimated cost-effectiveness in the presence of existing malaria interventions for vaccine prices of US$2-10 per dose. FINDINGS: In regions with a PfPR2-10 of 10-65%, RTS,S/AS01 is predicted to avert a median of 93,940 (range 20,490-126,540) clinical cases and 394 (127-708) deaths for the three-dose schedule, or 116,480 (31,450-160,410) clinical cases and 484 (189-859) deaths for the four-dose schedule, per 100,000 fully vaccinated children. A positive impact is also predicted at a PfPR2-10 of 5-10%, but there is little impact at a prevalence of lower than 3%. At $5 per dose and a PfPR2-10 of 10-65%, we estimated a median incremental cost-effectiveness ratio compared with current interventions of $30 (range 18-211) per clinical case averted and $80 (44-279) per DALY averted for the three-dose schedule, and of $25 (16-222) and $87 (48-244), respectively, for the four-dose schedule. Higher ICERs were estimated at low PfPR2-10 levels. INTERPRETATION: We predict a significant public health impact and high cost-effectiveness of the RTS,S/AS01 vaccine across a wide range of settings. Decisions about implementation will need to consider levels of malaria burden, the cost-effectiveness and coverage of other malaria interventions, health priorities, financing, and the capacity of the health system to deliver the vaccine. FUNDING: PATH Malaria Vaccine Initiative; Bill & Melinda Gates Foundation; Global Good Fund; Medical Research Council; UK Department for International Development; GAVI, the Vaccine Alliance; WHO.

The effect of polyploidy and hybridization on the evolution of floral colour in Nicotiana (Solanaceae).

BACKGROUND AND AIMS: Speciation in angiosperms can be accompanied by changes in floral colour that may influence pollinator preference and reproductive isolation. This study investigates whether changes in floral colour can accompany polyploid and homoploid hybridization, important processes in angiosperm evolution. METHODS: Spectral reflectance of corolla tissue was examined for 60 Nicotiana (Solanaceae) accessions (41 taxa) based on spectral shape (corresponding to pigmentation) as well as bee and hummingbird colour perception in order to assess patterns of floral colour evolution. Polyploid and homoploid hybrid spectra were compared with those of their progenitors to evaluate whether hybridization has resulted in floral colour shifts. KEY RESULTS: Floral colour categories in Nicotiana seem to have arisen multiple times independently during the evolution of the genus. Most younger polyploids displayed an unexpected floral colour, considering those of their progenitors, in the colour perception of at least one pollinator type, whereas older polyploids tended to resemble one or both of their progenitors. CONCLUSIONS: Floral colour evolution in Nicotiana is weakly constrained by phylogeny, and colour shifts do occur in association with both polyploid and homoploid hybrid divergence. Transgressive floral colour in N. tabacum has arisen by inheritance of anthocyanin pigmentation from its paternal progenitor while having a plastid phenotype like its maternal progenitor. Potentially, floral colour evolution has been driven by, or resulted in, pollinator shifts. However, those polyploids that are not sympatric (on a regional scale) with their progenitor lineages are typically not divergent in floral colour from them, perhaps because of a lack of competition for pollinators.

What is genetic differentiation, and how should we measure it--GST, D, neither or both?

Estimates of the fixation index, F(ST), have been used as measures of population differentiation for many decades. However, there have been persistent voices in the literature suggesting that these statistics do not measure true differentiation. In particular, the statistics Nei's G(ST) and Wier and Cockerham's θ have been criticized for being 'constrained' to not equal one in some situations that seem to represent maximal differentiation. Here, we address the issue of how to evaluate exactly how much information a particular statistic contains about the process of differentiation. This criterion can be used to counter most concerns about the performance of G(ST) (and related statistics), while also being reconciled with the insights of those who have proposed alternative measures of differentiation. In particular, the likelihood-based framework that we put forward can justify the use of G(ST) as an effective measure of differentiation, but also shows that in some situations G(ST) is insufficient on its own and needs supplementing by another measure such as Jost's D or Hedrick's G'(ST). This approach will become increasingly important in the future, as greater emphasis is placed on analysing large data sets.