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.

Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions.

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention ("lockdown") and reductions in individuals' mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies.

Malaria Transmission Dynamics in a High-Transmission Setting of Western Kenya and the Inadequate Treatment Response to Artemether-Lumefantrine in an Asymptomatic Population.

BACKGROUND: Assessing the infectious reservoir is critical in malaria control and elimination strategies. We conducted a longitudinal epidemiological study in a high-malaria-burden region in Kenya to characterize transmission in an asymptomatic population. METHODS: 488 study participants encompassing all ages in 120 households within 30 clusters were followed for 1 year with monthly sampling. Malaria was diagnosed by microscopy and molecular methods. Transmission potential in gametocytemic participants was assessed using direct skin and/or membrane mosquito feeding assays, then treated with artemether-lumefantrine. Study variables were assessed using mixed-effects generalized linear models. RESULTS: Asexual and sexual parasite data were collected from 3792 participant visits, with 903 linked with feeding assays. Univariate analysis revealed that the 6-11-year-old age group was at higher risk of harboring asexual and sexual infections than those <6 years old (odds ratio [OR] 1.68, P < .001; and OR 1.81, P < .001), respectively. Participants with submicroscopic parasitemia were at a lower risk of gametocytemia compared with microscopic parasitemia (OR 0.04, P < .001), but they transmitted at a significantly higher rate (OR 2.00, P = .002). A large proportion of the study population who were infected at least once remained infected (despite treatment) with asexual (71.7%, 291/406) or sexual (37.4%, 152/406) parasites. 88.6% (365/412) of feeding assays conducted in individuals who failed treatment the previous month resulted in transmissions. CONCLUSIONS: Individuals with asymptomatic infection sustain the transmission cycle, with the 6-11-year age group serving as an important reservoir. The high rates of artemether-lumefantrine treatment failures suggest surveillance programs using molecular methods need to be expanded for accurate monitoring and evaluation of treatment outcomes.

Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study.

BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality.

Understanding the Potential Impact of Different Drug Properties on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission and Disease Burden: A Modelling Analysis.

BACKGROUND: The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. METHODS: Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. RESULTS: The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. CONCLUSIONS: Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.

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.

Transmission of Artemisinin-Resistant Malaria Parasites to Mosquitoes under Antimalarial Drug Pressure.

Resistance to artemisinin-based combination therapy (ACT) in the Plasmodium falciparum parasite is threatening to reverse recent gains in reducing global deaths from malaria. While resistance manifests as delayed parasite clearance in patients, the phenotype can only spread geographically via the sexual stages and mosquito transmission. In addition to their asexual killing properties, artemisinin and its derivatives sterilize sexual male gametocytes. Whether resistant parasites overcome this sterilizing effect has not, however, been fully tested. Here, we analyzed P. falciparum clinical isolates from the Greater Mekong Subregion, each demonstrating delayed clinical clearance and known resistance-associated polymorphisms in the Kelch13 (PfK13var) gene. As well as demonstrating reduced asexual sensitivity to drug, certain PfK13var isolates demonstrated a marked reduction in sensitivity to artemisinin in an in vitro male gamete formation assay. Importantly, this same reduction in sensitivity was observed when the most resistant isolate was tested directly in mosquito feeds. These results indicate that, under artemisinin drug pressure, while sensitive parasites are blocked, resistant parasites continue transmission. This selective advantage for resistance transmission could favor acquisition of additional host-specificity or polymorphisms affecting partner drug sensitivity in mixed infections. Favored resistance transmission under ACT coverage could have profound implications for the spread of multidrug-resistant malaria beyond Southeast Asia.

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.

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.

Loss of function of parathyroid hormone receptor 1 induces Notch-dependent aortic defects during zebrafish vascular development.

OBJECTIVE: Coarctation of the aorta is rarely associated with known gene defects. Blomstrand chondrodysplasia, caused by mutations in the parathyroid hormone receptor 1 (PTHR1) is associated with coarctation of the aorta in some cases, although it is unclear whether PTHR1 deficiency causes coarctation of the aorta directly. The zebrafish allows the study of vascular development using approaches not possible in other models. We therefore examined the effect of loss of function of PTHR1 or its ligand parathyroid hormone-related peptide (PTHrP) on aortic formation in zebrafish. APPROACH AND RESULTS: Morpholino antisense oligonucleotide knockdown of either PTHR1 or PTHrP led to a localized occlusion of the mid-aorta in developing zebrafish. Confocal imaging of transgenic embryos showed that these defects were caused by loss of endothelium, rather than failure to lumenize. Using a Notch reporter transgenic ([CSL:Venus]qmc61), we found both PTHR1 and PTHrP knockdown-induced defective Notch signaling in the hypochord at the site of the aortic defect before onset of circulation, and the aortic occlusion was rescued by inducible Notch upregulation. CONCLUSIONS: Loss of function of either PTHR1 or PTHrP leads to a localized aortic defect that is Notch dependent. These findings may underlie the aortic defect seen in Blomstrand chondrodysplasia, and reveal a link between parathyroid hormone and Notch signaling during aortic development.

Risk of selection and timelines for the continued spread of artemisinin and partner drug resistance in Africa.

The introduction of artemisinin combination therapies (ACTs) has significantly reduced the burden of Plasmodium falciparum malaria, yet the emergence of artemisinin partial resistance (ART-R) as well as partner drug resistance threatens these gains. Recent confirmations of prevalent de novo ART-R mutations in Africa, in particular in Rwanda, Uganda and Ethiopia, underscore the urgency of addressing this issue in Africa. Our objective is to characterise this evolving resistance landscape in Africa and understand the speed with which ART-R will continue to spread. We produce estimates of both ART-R and partner drug resistance by bringing together WHO, WWARN and MalariaGen Pf7k data on antimalarial resistance in combination with a literature review. We integrate these estimates within a mathematical modelling approach, aincorporating to estimate parameters known to impact the selection of ART-R for each malaria-endemic country and explore scenarios of ART-R spread and establishment. We identify 16 malaria-endemic countries in Africa to prioritise for surveillance and future deployment of alternative antimalarial strategies, based on ART-R reaching greater than 10% prevalence by 2040 under current malaria burden and effective-treatment coverage. If resistance continues to spread at current rates with no change in drug policy, we predict that partner drug resistance will emerge and the mean percentage of treatment failure across Africa will reach 30.74% by 2060 (parameter uncertainty range: 24.98% - 34.54%). This translates to an alarming number of treatment failures, with 52,980,600 absolute cases of treatment failure predicted in 2060 in Africa (parameter uncertainty range: 26,374,200 - 93,672,400) based on current effective treatment coverage. Our results provide a refined and updated prediction model for the emergence of ART-R to help guide antimalarial policy and prioritise future surveillance efforts and innovation in Africa. These results put into stark context the speed with which antimalarial resistance may spread in Africa if left unchecked, confirming the need for swift and decisive action in formulating antimalarial treatment policies focused on furthering malaria control and containing antimalarial resistance in Africa. The rise of artemisinin partial resistance (ART-R) and increasing partner drug tolerance by Plasmodium falciparum malaria in Africa threatens to undo malaria control efforts. Recent confirmations of de novo ART-R markers in Rwanda, Uganda, and Ethiopia highlight the urgent need to address this threat in Africa, where the vast majority of cases and deaths occur. This study characterises the resistance landscape and predicts the spread of antimalarial resistance across Africa. We estimate and map the current levels of resistance markers related to artemisinin and its partner drugs using WHO, WWARN, and MalariaGen Pf7k data. We combine these estimates with current malaria transmission and treatment data and use an established individual-based model of malaria resistance to simulate future resistance spread. We identify 16 African countries at highest risk of ART-R for prioritisation of enhanced surveillance and alternative antimalarial strategies. We project that, without policy changes, ART-R will exceed 10% in these regions by 2040. By 2060, if resistance spreads unchecked, we predict mean treatment failure rates will reach 30.74% (parameter uncertainty range: 24.98% - 34.54%) across Africa. This alarming spread of resistance is predicted to cause 52.98 million treatment failures (uncertainty range: 26.37 million - 93.67 million) in 2060. The impact of antimalarial resistance in Africa, if left unchecked, would hugely damage efforts to reduce malaria burden. Our results underscore the critical need for swift policy action to contain resistance and guide future surveillance and intervention efforts.

Selection of artemisinin partial resistance Kelch13 mutations in Uganda in 2016-22 was at a rate comparable to that seen previously in South-East Asia.

Background: Artemisinin partial resistance, mediated by mutations in the Plasmodium falciparum Kelch13 protein (K13), rapidly spread in South-East Asia (SEA), undermining antimalarial efficacies of artemisinin-based combination therapies (ACT). Validated K13 mutations have recently arisen in Africa, but rates of increase are not well characterized. Methods: We investigated K13 mutation prevalence at 16 sites in Uganda (2016-2022, 6586 samples), and five sites in SEA (2003-2018, 5465 samples) by calculating selection coefficients using Bayesian mixed-effect linear models. We then tested whether SEA K13 mutation prevalence could have been forecast accurately using up to the first five years of available data and forecast future K13 mutation prevalence in Uganda. Findings: The selection coefficient for the prevalence of relevant K13 mutations (441L, 469F/Y, 561H, 675V) was estimated at s=0·383 (95% CrI: 0·247 - 0·528) per year, a 38% relative prevalence increase. Selection coefficients across Uganda were s=0·968 (0·463 - 1·569) for 441L, s=0·153 (-0·445 - 0·727) for 469F, s=0·222 (-0·011 - 0·398) for 469Y, and s=0·152 (-0·023 - 0·312) for 675V. In SEA, the selection coefficient was s=-0·005 (-0·852 - 0·814) for 539T, s=0·574 (-0·092 - 1·201) for 580Y, and s=0·308 (0·089 - 0·536) for all validated K13 mutations. Forecast prevalences for Uganda assuming constant selection neared fixation (>95% prevalence) within a decade (2028-2033) for combined K13 mutations. Interpretation: The selection of K13 mutations in Uganda was at a comparable rate to that observed in SEA, suggesting K13 mutations may continue to increase quickly in Uganda. Funding: NIH R01AI156267, R01AI075045, and R01AI089674.

Global risk of selection and spread of Plasmodium falciparum histidine-rich protein 2 and 3 gene deletions.

In the thirteen years since the first report of pfhrp2-deleted parasites in 2010, the World Health Organization (WHO) has found that 40 of 47 countries surveyed worldwide have reported pfhrp2/3 gene deletions. Due to a high prevalence of pfhrp2/3 deletions causing false-negative HRP2 RDTs, in the last five years, Eritrea, Djibouti and Ethiopia have switched or started switching to using alternative RDTs, that target pan-specific-pLDH or P. falciparum specific-pLDH alone of in combination with HRP2. However, manufacturing of alternative RDTs has not been brought to scale and there are no WHO prequalified combination tests that use Pf-pLDH instead of HRP2 for P. falciparum detection. For these reasons, the continued spread of pfhrp2/3 deletions represents a growing public health crisis that threatens efforts to control and eliminate P. falciparum malaria. National malaria control programmes, their implementing partners and test developers desperately seek pfhrp2/3 deletion data that can inform their immediate and future resource allocation. In response, we use a mathematical modelling approach to evaluate the global risk posed by pfhrp2/3 deletions and explore scenarios for how deletions will continue to spread in Africa. We incorporate current best estimates of the prevalence of pfhrp2/3 deletions and conduct a literature review to estimate model parameters known to impact the selection of pfhrp2/3 deletions for each malaria endemic country. We identify 20 countries worldwide to prioritise for surveillance and future deployment of alternative RDT, based on quickly selecting for pfhrp2/3 deletions once established. In scenarios designed to explore the continued spread of deletions in Africa, we identify 10 high threat countries that are most at risk of deletions both spreading to and subsequently being rapidly selected for. If HRP2-based RDTs continue to be relied on for malaria case management, we predict that the major route for pfhrp2 deletions to spread is south out from the current hotspot in the Horn of Africa, moving through East Africa over the next 20 years. We explore the variation in modelled timelines through an extensive parameter sensitivity analysis and despite wide uncertainties, we identify three countries that have not yet switched RDTs (Senegal, Zambia and Kenya) that are robustly identified as high risk for pfhrp2/3 deletions. These results provide a refined and updated prediction model for the emergence of pfhrp2/3 deletions in an effort to help guide pfhrp2/3 policy and prioritise future surveillance efforts and innovation.

Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach.

With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the ancestral vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness.