Seasonal dynamics of Anopheles stephensi and its implications for mosquito detection and emergent malaria control in the Horn of Africa.

Invasion of the malaria vector Anopheles stephensi across the Horn of Africa threatens control efforts across the continent, particularly in urban settings where the vector is able to proliferate. Malaria transmission is primarily determined by the abundance of dominant vectors, which often varies seasonally with rainfall. However, it remains unclear how An. stephensi abundance changes throughout the year, despite this being a crucial input to surveillance and control activities. We collate longitudinal catch data from across its endemic range to better understand the vector's seasonal dynamics and explore the implications of this seasonality for malaria surveillance and control across the Horn of Africa. Our analyses reveal pronounced variation in seasonal dynamics, the timing and nature of which are poorly predicted by rainfall patterns. Instead, they are associated with temperature and patterns of land use; frequently differing between rural and urban settings. Our results show that timing entomological surveys to coincide with rainy periods is unlikely to improve the likelihood of detecting An. stephensi. Integrating these results into a malaria transmission model, we show that timing indoor residual spraying campaigns to coincide with peak rainfall offers little improvement in reducing disease burden compared to starting in a random month. Our results suggest that unlike other malaria vectors in Africa, rainfall may be a poor guide to predicting the timing of peaks in An. stephensi-driven malaria transmission. This highlights the urgent need for longitudinal entomological monitoring of the vector in its new environments given recent invasion and potential spread across the continent.

Diagnostic Performance of Loop-Mediated Isothermal Amplification and Ultrasensitive Rapid Diagnostic Tests for Malaria Screening Among Pregnant Women in Kenya.

BACKGROUND: Screen-and-treat strategies with sensitive diagnostic tests may reduce malaria-associated adverse pregnancy outcomes. We conducted a diagnostic accuracy study to evaluate new point-of-care tests to screen pregnant women for malaria at their first antenatal visit in western Kenya. METHODS: Consecutively women were tested for Plasmodium infection by expert microscopy, conventional rapid diagnostic test (cRDT), ultra sensitive RDT (usRDT), and loop-mediated isothermal amplification (LAMP). Photoinduced electron-transfer polymerase chain reaction (PET-PCR) served as the reference standard. Diagnostic performance was calculated and modelled at low parasite densities. RESULTS: Between May and September 2018, 172 of 482 screened participants (35.7%) were PET-PCR positive. Relative to PET-PCR, expert microscopy was least sensitive (40.1%; 95% confidence interval [CI], 32.7%-47.9%), followed by cRDT (49.4%; 95% CI, 41.7%-57.1), usRDT (54.7%; 95% CI, 46.9%-62.2%), and LAMP (68.6%; 95% CI, 61.1%-75.5%). Test sensitivities were comparable in febrile women (n = 90). Among afebrile women (n = 392), the geometric-mean parasite density was 29 parasites/µL and LAMP (sensitivity = 61.9%) and usRDT (43.2%) detected 1.74 (95% CI, 1.31-2.30) and 1.21 (95% CI, 88-2.21) more infections than cRDT (35.6%). Per our model, tests performed similarly at densities >200 parasites/µL. At 50 parasites/µL, the sensitivities were 45%, 56%, 62%, and 74% with expert microscopy, cRDT, usRDT, and LAMP, respectively. CONCLUSIONS: This first-generation usRDT provided moderate improvement in detecting low-density infections in afebrile pregnant women compared to cRDTs.

Health inequities and clustering of fever, acute respiratory infection, diarrhoea and wasting in children under five in low- and middle-income countries: a Demographic and Health Surveys analysis.

BACKGROUND: Pneumonia, diarrhoea and malaria are responsible for over one third of all deaths in children under the age of 5 years in low and middle sociodemographic index countries; many of these deaths are also associated with malnutrition. We explore the co-occurrence and clustering of fever, acute respiratory infection, diarrhoea and wasting and their relationship with equity-relevant variables. METHODS: Multilevel, multivariate Bayesian logistic regression models were fitted to Demographic and Health Survey data from over 380,000 children in 39 countries. The relationship between outcome indicators (fever, acute respiratory infection, diarrhoea and wasting) and equity-relevant variables (wealth, access to health care and rurality) was examined. We quantified the geographical clustering and co-occurrence of conditions and a child's risk of multiple illnesses. RESULTS: The prevalence of outcomes was very heterogeneous within and between countries. There was marked spatial clustering of conditions and co-occurrence within children. For children in the poorest households and those reporting difficulties accessing healthcare, there were significant increases in the probability of at least one of the conditions in 18 of 21 countries, with estimated increases in the probability of up to 0.23 (95% CrI, 0.06-0.40). CONCLUSIONS: The prevalence of fever, acute respiratory infection, diarrhoea and wasting are associated with equity-relevant variables and cluster together. Via pathways of shared aetiology or risk, those children most disadvantaged disproportionately suffer from these conditions. This highlights the need for horizontal approaches, such as integrated community case management, with a focus on equity and targeted to those most at need.

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.

Comparison of diagnostics for the detection of asymptomatic Plasmodium falciparum infections to inform control and elimination strategies.

The global burden of malaria has been substantially reduced over the past two decades. Future efforts to reduce malaria further will require moving beyond the treatment of clinical infections to targeting malaria transmission more broadly in the community. As such, the accurate identification of asymptomatic human infections, which can sustain a large proportion of transmission, is becoming a vital component of control and elimination programmes. We determined the relationship across common diagnostics used to measure malaria prevalence - polymerase chain reaction (PCR), rapid diagnostic test and microscopy - for the detection of Plasmodium falciparum infections in endemic populations based on a pooled analysis of cross-sectional data. We included data from more than 170,000 individuals comparing the detection by rapid diagnostic test and microscopy, and 30,000 for detection by rapid diagnostic test and PCR. The analysis showed that, on average, rapid diagnostic tests detected 41% (95% confidence interval = 26-66%) of PCR-positive infections. Data for the comparison of rapid diagnostic test to PCR detection at high transmission intensity and in adults were sparse. Prevalence measured by rapid diagnostic test and microscopy was comparable, although rapid diagnostic test detected slightly more infections than microscopy. On average, microscopy captured 87% (95% confidence interval = 74-102%) of rapid diagnostic test-positive infections. The extent to which higher rapid diagnostic test detection reflects increased sensitivity, lack of specificity or both, is unclear. Once the contribution of asymptomatic individuals to the infectious reservoir is better defined, future analyses should ideally establish optimal detection limits of new diagnostics for use in control and elimination strategies.

Assessing the impact of next-generation rapid diagnostic tests on Plasmodium falciparum malaria elimination strategies.

Mass-screen-and-treat and targeted mass-drug-administration strategies are being considered as a means to interrupt transmission of Plasmodium falciparum malaria. However, the effectiveness of such strategies will depend on the extent to which current and future diagnostics are able to detect those individuals who are infectious to mosquitoes. We estimate the relationship between parasite density and onward infectivity using sensitive quantitative parasite diagnostics and mosquito feeding assays from Burkina Faso. We find that a diagnostic with a lower detection limit of 200 parasites per microlitre would detect 55% of the infectious reservoir (the combined infectivity to mosquitoes of the whole population weighted by how often each individual is bitten) whereas a test with a limit of 20 parasites per microlitre would detect 83% and 2 parasites per microlitre would detect 95% of the infectious reservoir. Using mathematical models, we show that increasing the diagnostic sensitivity from 200 parasites per microlitre (equivalent to microscopy or current rapid diagnostic tests) to 2 parasites per microlitre would increase the number of regions where transmission could be interrupted with a mass-screen-and-treat programme from an entomological inoculation rate below 1 to one of up to 4. The higher sensitivity diagnostic could reduce the number of treatment rounds required to interrupt transmission in areas of lower prevalence. We predict that mass-screen-and-treat with a highly sensitive diagnostic is less effective than mass drug administration owing to the prophylactic protection provided to uninfected individuals by the latter approach. In low-transmission settings such as those in Southeast Asia, we find that a diagnostic tool with a sensitivity of 20 parasites per microlitre may be sufficient for targeted mass drug administration because this diagnostic is predicted to identify a similar village population prevalence compared with that currently detected using polymerase chain reaction if treatment levels are high and screening is conducted during the dry season. Along with other factors, such as coverage, choice of drug, timing of the intervention, importation of infections, and seasonality, the sensitivity of the diagnostic can play a part in increasing the chance of interrupting transmission.

Estimated impact on birth weight of scaling up intermittent preventive treatment of malaria in pregnancy given sulphadoxine-pyrimethamine resistance in Africa: A mathematical model.

BACKGROUND: Malaria transmission has declined substantially in the 21st century, but pregnant women in areas of sustained transmission still require protection to prevent the adverse pregnancy and birth outcomes associated with malaria in pregnancy (MiP). A recent call to action has been issued to address the continuing low coverage of intermittent preventive treatment of malaria in pregnancy (IPTp). This call has, however, been questioned by some, in part due to concerns about resistance to sulphadoxine-pyrimethamine (SP), the only drug currently recommended for IPTp. METHODS AND FINDINGS: Using an existing mathematical model of MiP, we combined estimates of the changing endemicity of malaria across Africa with maps of SP resistance mutations and current coverage of antenatal access and IPTp with SP (IPTp-SP) across Africa. Using estimates of the relationship between SP resistance mutations and the parasitological efficacy of SP during pregnancy, we estimated the varying impact of IPTp-SP across Africa and the incremental value of enhancing IPTp-SP uptake to match current antenatal care (ANC) coverage. The risks of MiP and malaria-attributable low birthweight (mLBW) in unprotected pregnancies (i.e., those not using insecticide-treated nets [ITNs]) leading to live births fell by 37% (33%-41% 95% credible interval [crI]) and 31% (27%-34% 95% crI), respectively, from 2000 to 2015 across endemic areas in sub-Saharan Africa. However, these gains are fragile, and coverage is far from optimal. In 2015, 9.5 million (8.3 million-10.4 million 95% crI) of 30.6 million pregnancies in these areas would still have been infected with Plasmodium falciparum without intervention, leading to 750,000 (390,000-1.1 million 95% crI) mLBW deliveries. In all, 6.6 million (5.6 million-7.3 million 95% crI) of these 9.5 million (69.3%) pregnancies at risk of infection (and 53.4% [16.3 million/30.6 million] of all pregnancies) occurred in settings with near-perfect SP curative efficacy (>99%) based on the most recent estimates of resistance. Forty-four percent of these pregnancies (23% of all pregnancies) were not receiving any IPTp-SP despite making ≥3 ANC visits, representing 160,000 (94,000-236,000 95% crI) preventable low birthweight (LBW) deliveries. Only 4% (1.4 million) of pregnancies occurred in settings with >10% prevalence of the sextuple haplotype associated with compromised SP effectiveness. Forty-two percent of all pregnancies occurred in settings where the quintuple dhfr/dhps haplotype had become established but where in vivo efficacy data suggest SP maintains the majority of its effectiveness in clearing infections. Not accounting for protection from the use of ITNs during pregnancy, expanding IPTp-SP to all women with ≥3 ANC visits in Africa could prevent an additional 215,000 (128,000-318,000 95% crI) LBW deliveries. In 26 countries with sufficient recent data to estimate ITN impact (population-based ITN usage data that can be stratified by gravidity), we estimate that, due primarily to low ITN use by primigravidae, only 16.5% of the potential LBW births prevented by scaling up IPTp-SP would in fact have already have been prevented through ITN use. Our analysis also highlights the difficulties associated with estimating the relationship between the effectiveness of interventions against parasitological endpoints such as placental infection at delivery and health outcomes including birthweight, which is also determined by a wide range of unrelated factors. We also did not capture other aspects of malaria burden such as clinical malaria, maternal and neonatal anaemia, and miscarriage, all of which increase the overall importance of effective preventative strategies but have their own relationship with transmission intensity, parity, and SP resistance. CONCLUSIONS: Despite recent declines in malaria transmission in Africa, the burden of MiP in the absence of adequate prevention remains substantial. Even accounting for SP resistance, extending IPTp-SP to all women attending ANC, as well as long-lasting insecticidal net distribution targeted towards first-time mothers, would have a sizeable impact upon maternal and infant health in almost all malaria-endemic settings in sub-Saharan Africa.

The US President's Malaria Initiative, Plasmodium falciparum transmission and mortality: A modelling study.

BACKGROUND: Although significant progress has been made in reducing malaria transmission globally in recent years, a large number of people remain at risk and hence the gains made are fragile. Funding lags well behind amounts needed to protect all those at risk and ongoing contributions from major donors, such as the President's Malaria Initiative (PMI), are vital to maintain progress and pursue further reductions in burden. We use a mathematical modelling approach to estimate the impact of PMI investments to date in reducing malaria burden and to explore the potential negative impact on malaria burden should a proposed 44% reduction in PMI funding occur. METHODS AND FINDINGS: We combined an established mathematical model of Plasmodium falciparum transmission dynamics with epidemiological, intervention, and PMI-financing data to estimate the contribution PMI has made to malaria control via funding for long-lasting insecticide treated nets (LLINs), indoor residual spraying (IRS), and artemisinin combination therapies (ACTs). We estimate that PMI has prevented 185 million (95% CrI: 138 million, 230 million) malaria cases and saved 940,049 (95% CrI: 545,228, 1.4 million) lives since 2005. If funding is maintained, PMI-funded interventions are estimated to avert a further 162 million (95% CrI: 116 million, 194 million) cases, saving a further 692,589 (95% CrI: 392,694, 955,653) lives between 2017 and 2020. With an estimate of US$94 (95% CrI: US$51, US$166) per Disability Adjusted Life Year (DALY) averted, PMI-funded interventions are highly cost-effective. We also demonstrate the further impact of this investment by reducing caseloads on health systems. If a 44% reduction in PMI funding were to occur, we predict that this loss of direct aid could result in an additional 67 million (95% CrI: 49 million, 82 million) cases and 290,649 (95% CrI: 167,208, 395,263) deaths between 2017 and 2020. We have not modelled indirect impacts of PMI funding (such as health systems strengthening) in this analysis. CONCLUSIONS: Our model estimates that PMI has played a significant role in reducing malaria cases and deaths since its inception. Reductions in funding to PMI could lead to large increases in the number of malaria cases and deaths, damaging global goals of malaria control and elimination.

Seasonality in malaria transmission: implications for case-management with long-acting artemisinin combination therapy in sub-Saharan Africa.

BACKGROUND: Long-acting artemisinin-based combination therapy (LACT) offers the potential to prevent recurrent malaria attacks in highly exposed children. However, it is not clear where this advantage will be most important, and deployment of these drugs is not rationalized on this basis. METHODS: To understand where post-treatment prophylaxis would be most beneficial, the relationship between seasonality, transmission intensity and the interval between malaria episodes was explored using data from six cohort studies in West Africa and an individual-based malaria transmission model. The total number of recurrent malaria cases per 1000 child-years at risk, and the fraction of the total annual burden that this represents were estimated for sub-Saharan Africa. RESULTS: In settings where prevalence is less than 10 %, repeat malaria episodes constitute a small fraction of the total burden, and few repeat episodes occur within the window of protection provided by currently available drugs. However, in higher transmission settings, and particularly in high transmission settings with highly seasonal transmission, repeat malaria becomes increasingly important, with up to 20 % of the total clinical burden in children estimated to be due to repeat episodes within 4 weeks of a prior attack. CONCLUSION: At a given level of transmission intensity and annual incidence, the concentration of repeat malaria episodes in time, and consequently the protection from LACT is highest in the most seasonal areas. As a result, the degree of seasonality, in addition to the overall intensity of transmission, should be considered by policy makers when deciding between ACT that differ in their duration of post-treatment prophylaxis.

The potential impact of adding ivermectin to a mass treatment intervention to reduce malaria transmission: a modelling study.

BACKGROUND: Ivermectin (IVM), used alongside mass treatment strategies with an artemisinin combination therapy, has been suggested as a possible tool for reducing malaria transmission. Mosquitoes ingesting a bloodmeal containing IVM have increased mortality, reducing the probability that the parasite completes sporogony. METHODS: Human pharmacokinetic data and mortality data for mosquitoes taking bloodmeals containing IVM are used to quantify the mosquitocidal effect of IVM. These are incorporated into a transmission model to estimate the impact of IVM in combination with mass treatment strategies with artemether-lumefantrine on transmission metrics. RESULTS: Adding IVM increases the reductions in parasite prevalence achieved and delays the reemergence of parasites compared to mass treatment alone. This transmission effect is obtained through its effect on vector mortality. IVM effectiveness depends on coverage with the highest impact achieved if given to the whole population rather than only those with existing detectable parasites. Our results suggest that including IVM in a mass treatment strategy can reduce the time taken to interrupt transmission as well as help to achieve transmission interruption in transmission settings in which mass treatment strategies alone would be insufficient. CONCLUSIONS: Including IVM in mass treatment strategies could be a useful adjunct to reduce and interrupt malaria transmission.

Assessing the utility of pregnant women as a sentinel surveillance population for malaria in Geita, Tanzania, 2019 - 2021.

OBJECTIVES: Estimates of malaria burden and intervention uptake in Africa are primarily based on household surveys. However, their expense and infrequency limit their utility. We investigated whether data collected during antenatal care (ANC) can provide relevant information for decision-makers. METHODS: Malaria test positivity rates and questionnaire data from ANC attendees at 39 health facilities were compared to questionnaire data and positivity rates among children from two cross-sectional surveys in the facilities' corresponding catchment areas. RESULTS: Trends in parasitemia among ANC attendees were predictive of trends in parasitemia among children at the council level (mean absolute error 6.0%). Primigravid ANC attendees had the lowest rates of net ownership (modeled odds ratio [OR] 0.28, 95% CI 0.19-0.40) and use (OR 0.58, 95% CI 0.42-0.79). ANC attendees reported higher levels of care-seeking (OR 1.78, 95% CI 1.48-2.14), malaria testing (OR 4.16, 95% CI 3.44-5.04), and treatment for children with fever (OR 7.66, 95% CI 4.89-11.98) compared to women surveyed in households, raising concerns about social desirability bias disproportionately impacting ANC surveys. CONCLUSION: ANC surveillance is an effective strategy for tracking trends in malaria burden. More work is required to elucidate the value of administering questionnaires to ANC attendees.

Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context.

Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2 prevalence data during 2020 allow estimation of excess mortality and transmission. Relative to pre-pandemic patterns, we estimate age-dependent mortality increases, totalling 3212 excess deaths (95% CrI: 2104-4591), representing an 18.5% (95% CrI: 13.0-25.2%) increase relative to pre-pandemic levels. Using a dynamical model-based inferential framework, we find that these mortality patterns and SARS-CoV-2 prevalence data are in agreement with established COVID-19 severity estimates. Our results support hypotheses that COVID-19 impact in Lusaka during 2020 was consistent with COVID-19 epidemics elsewhere, without requiring exceptional explanations for low reported figures. For more equitable decision-making during future pandemics, barriers to ascertaining attributable mortality in low-income settings must be addressed and factored into discourse around reported impact differences.

Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems.

Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media-conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide.

Seasonal use case for the RTS,S/AS01 malaria vaccine: a mathematical modelling study.

BACKGROUND: A 2021 clinical trial of seasonal RTS,S/AS01E (RTS,S) vaccination showed that vaccination was non-inferior to seasonal malaria chemoprevention (SMC) in preventing clinical malaria. The combination of these two interventions provided significant additional protection against clinical and severe malaria outcomes. Projections of the effect of this novel approach to RTS,S vaccination in seasonal transmission settings for extended timeframes and across a range of epidemiological settings are needed to inform policy recommendations. METHODS: We used a mathematical, individual-based model of malaria transmission that was fitted to data on the relationship between entomological inoculation rate and parasite prevalence, clinical disease, severe disease, and deaths from multiple sites across Africa. The model was validated with results from a phase 3b trial assessing the effect of SV-RTS,S in Mali and Burkina Faso. We developed three intervention efficacy models with varying degrees and durations of protection for our population-level modelling analysis to assess the potential effect of an RTS,S vaccination schedule based on age (doses were delivered to children aged 6 months, 7·5 months, and 9 months for the first three doses, and at 27 months of age for the fourth dose) or season (children aged 5-17 months at the time of first vaccination received the first three doses in the 3 months preceding the transmission season, with any subsequent doses up to five doses delivered annually) in seasonal transmission settings both in the absence and presence of SMC with sulfadoxine-pyrimethamine plus amodiaquine. This is modelled as a full therapeutic course delivered every month for four or five months of the peak in transmission season. Estimates of cases and deaths averted in a population of 100 000 children aged 0-5 years were calculated over a 15-year time period for a range of levels of malaria transmission intensity (Plasmodium falciparum parasite prevalence in children aged 2-10 years between 10% and 65%) and over two west Africa seasonality archetypes. FINDINGS: Seasonally targeting RTS,S resulted in greater absolute reductions in malaria cases and deaths compared with an age-based strategy, averting an additional 14 000-47 000 cases per 100 000 children aged 5 years and younger over 15 years, dependent on seasonality and transmission intensity. We predicted that adding seasonally targeted RTS,S to SMC would reduce clinical incidence by up to an additional 42 000-67 000 cases per 100 000 children aged 5 years and younger over 15 years compared with SMC alone. Transmission season duration was a key determinant of intervention effect, with the advantage of adding RTS,S to SMC predicted to be smaller with shorter transmission seasons. INTERPRETATION: RTS,S vaccination in seasonal settings could be a valuable additional tool to existing interventions, with seasonal delivery maximising the effect relative to an age-based approach. Decisions surrounding deployment strategies of RTS,S in such settings will need to consider the local and regional variations in seasonality, current rates of other interventions, and potential achievable RTS,S coverage. FUNDING: UK Medical Research Council, UK Foreign Commonwealth & Development Office, The Wellcome Trust, and The Royal society.

Global estimates of pregnancies at risk of Plasmodium falciparum and Plasmodium vivax infection in 2020 and changes in risk patterns since 2000.

BACKGROUND: Women are at risk of severe adverse pregnancy outcomes attributable to Plasmodium spp. infection in malaria-endemic areas. Malaria control efforts since 2000 have aimed to reduce this burden of disease. METHODS: We used data from the Malaria Atlas Project and WorldPop to calculate global pregnancies at-risk of Plasmodium spp. infection. We categorised pregnancies as occurring in areas of stable and unstable P. falciparum and P. vivax transmission. We further stratified stable endemicity as hypo-endemic, meso-endemic, hyper-endemic, or holo-endemic, and estimated pregnancies at risk in 2000, 2005, 2010, 2015, 2017, and 2020. FINDINGS: In 2020, globally 120.4M pregnancies were at risk of P. falciparum, two-thirds (81.0M, 67.3%) were in areas of stable transmission; 85 2M pregnancies were at risk of P. vivax, 93.9% (80.0M) were in areas of stable transmission. An estimated 64.6M pregnancies were in areas with both P. falciparum and P. vivax transmission. The number of pregnancies at risk of each of P. falciparum and P. vivax worldwide decreased between 2000 and 2020, with the exception of sub-Saharan Africa, where the total number of pregnancies at risk of P. falciparum increased from 37 3M in 2000 to 52 4M in 2020. INTERPRETATION: Historic investments in malaria control have reduced the number of women at risk of malaria in pregnancy in all endemic regions except sub-Saharan Africa. Population growth in Africa has outpaced reductions in malaria prevalence. Interventions that reduce the risk of malaria in pregnancy are needed as much today as ever.

Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling.

Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49-2.53%. Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.

A Bayesian approach to quantifying the effects of mass poultry vaccination upon the spatial and temporal dynamics of H5N1 in Northern Vietnam.

Outbreaks of H5N1 in poultry in Vietnam continue to threaten the livelihoods of those reliant on poultry production whilst simultaneously posing a severe public health risk given the high mortality associated with human infection. Authorities have invested significant resources in order to control these outbreaks. Of particular interest is the decision, following a second wave of outbreaks, to move from a "stamping out" approach to the implementation of a nationwide mass vaccination campaign. Outbreaks which occurred around this shift in policy provide a unique opportunity to evaluate the relative effectiveness of these approaches and to help other countries make informed judgements when developing control strategies. Here we use Bayesian Markov Chain Monte Carlo (MCMC) data augmentation techniques to derive the first quantitative estimates of the impact of the vaccination campaign on the spread of outbreaks of H5N1 in northern Vietnam. We find a substantial decrease in the transmissibility of infection between communes following vaccination. This was coupled with a significant increase in the time from infection to detection of the outbreak. Using a cladistic approach we estimated that, according to the posterior mean effect of pruning the reconstructed epidemic tree, two thirds of the outbreaks in 2007 could be attributed to this decrease in the rate of reporting. The net impact of these two effects was a less intense but longer-lasting wave and, whilst not sufficient to prevent the sustained spread of outbreaks, an overall reduction in the likelihood of the transmission of infection between communes. These findings highlight the need for more effectively targeted surveillance in order to help ensure that the effective coverage achieved by mass vaccination is converted into a reduction in the likelihood of outbreaks occurring which is sufficient to control the spread of H5N1 in Vietnam.

Communicating uncertainty in epidemic models.

While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.

Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: A mathematical modelling analysis.

The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extend a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identify optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We find that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, and the level of healthcare available to effectively treat those with disease. Within a country we find that for a limited supply (doses for < 20% of the population) the optimal strategy is to target the elderly. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.

Reduction in mobility and COVID-19 transmission.

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.