The emergence of antimalarial drug resistance is a major threat to malaria control and elimination. Using whole genome sequencing of 282 P. falciparum samples collected during the 2018 Zambia National Malaria Indicator Survey, we determined the prevalence and spatial distribution of known and candidate antimalarial drug resistance mutations. High levels of genotypic resistance were found across Zambia to pyrimethamine, with over 94% (n=266) of samples having the Pfdhfr triple mutant (N51I, C59R, and S108N), and sulfadoxine, with over 84% (n=238) having the Pfdhps double mutant (A437G and K540E). In northern Zambia, 5.3% (n=15) of samples also harbored the Pfdhps A581G mutation. Although 29 mutations were identified in Pfkelch13, these mutations were present at low frequency (<2.5%), and only three were WHO-validated artemisinin partial resistance mutations: P441L (n=1, 0.35%), V568M (n=2, 0.7%) and R622T (n=1, 0.35%). Notably, 91 (32%) of samples carried the E431K mutation in the Pfatpase6 gene, which is associated with artemisinin resistance. No specimens carried any known mutations associated with chloroquine resistance in the Pfcrt gene (codons 72-76). P. falciparum strains circulating in Zambia were highly resistant to sulfadoxine and pyrimethamine but remained susceptible to chloroquine and artemisinin. Despite this encouraging finding, early genetic signs of developing artemisinin resistance highlight the urgent need for continued vigilance and expanded routine genomic surveillance to monitor these changes.

Quantifying population mobility is crucial in developing accurate models of infectious disease dynamics. Increasingly, multiple data sources are available to describe individual and population mobility in a single location; however, there are no methods to systematically integrate these data. Combining information from these data sets may be valuable and help mitigate inherent biases in each data set due to sampling, censoring, and recall. We examined four commonly used data sources (mobile phone records, travel survey, Demographic and Health Survey, and Facebook location information) to quantify subnational travel patterns in Zambia. First, we explored summary metrics of mobility from each data set. Estimates of the probability of a trip and location of travel varied across data sets, with some data quantifying twice the frequency of travel as others. Then, we developed a departure-diffusion model that is able to produce a single estimate of travel by combining these data sets. When multi-data set models included mobile phone records, this data source dominated estimates given the broader spatial coverage. We then used a metapopulation model to simulate a measles outbreak to identify how these different data sets and models would impact estimates of the spatial spread of a highly infectious disease. We found that using travel survey data to parameterize mobility resulted in the introduction of cases in 98% of districts compared to less than 50% when mobile phone data or Facebook data were used. This study highlights the need for methods that facilitate integrating multiple data sets to improve validity of mobility estimates and resultant infectious disease transmission dynamics.

BACKGROUND:Enteric infections are a leading cause of global morbidity and mortality, with the highest burden of disease in young children in low- and middle-income countries. Comprehensive profiling of enteric infections, which requires intensive sampling and molecular and culture-based detection methods, may miss recent and historical infections. High-throughput antibody-based testing of blood or non-invasive specimens like saliva can fill this gap, especially in vulnerable populations. METHODS:We developed a bead-based multiplex immunoassay (MIA) that includes enteric pathogen targets from bacteria (Shigella, Enterotoxigenic Escherichia coli [ETEC], Campylobacter, typhoidal Salmonella, non-typhoidal Salmonella); viruses (norovirus, rotavirus, hepatitis E virus, adenovirus, astrovirus); and protozoa (Cryptosporidium, Giardia), as well as select targets for respiratory viruses and vaccine preventable diseases (VPDs). Coupling was optimized for peptide and lipopolysaccharide (LPS) antigens separately and assay performance characterized for both serum and salivary applications. RESULTS:The ability to assess IgG and IgA antibody responses in serum ranging over 4 orders of magnitude was demonstrated, allowing for assessment of various phases of infection. The mean inter-operator assay precision was excellent (6.7 % CV in serum IgG and 10.6 % CV in saliva IgG). The MIA was highly correlated (r = 0.72-0.96, p < 0.0001) with reference ELISA antibody titers in selected antigens. CONCLUSIONS:Improved scalability of enteric pathogen detection through an MIA may be combined with existing serosurveillance for VPDs and respiratory viruses and complement broad enteric pathogen burden and vaccine studies. This framework for integrated serology provides methods for assessing disease burden to inform prevention and treatment guidelines and guide targeted interventions.

The Immunization and Vaccines-related Implementation Research Advisory Committee (IVIR-AC) is the primary advisory body of the World Health Organization conducting independent reviews of immunization-related implementation research, with a primary focus on transmission and economic modeling analyses that estimate the value and impact of vaccines. From 10 to 13th September 2024, IVIR-AC convened virtually for its second of two semi-annual meetings to provide feedback and recommendations across six sessions including: pneumococcal vaccination strategies that rely on indirect protection; vaccine impact modeling for chikungunya; The Lancet Commission on strengthening the use of epidemiological modeling of emerging and pandemic infectious diseases; methods for immunization coverage estimation; setting immunization research priorities in the South-East Asian Region; and modeling evidence related to typhoid conjugate vaccine schedules. This report summarizes the sessions, proceedings, and recommendations from that meeting.

Background: Geographic information systems (GIS) are a promising tool for mapping vaccination coverage and identifying missed communities, yet their use in low- and middle-income countries (LMICs) remains limited. In settings without standardized addresses such as schools or outreach sites, innovative methods are needed to collect and analyse spatial data. Schools offer a unique platform for identifying under-vaccinated children missed by routine or campaign efforts. Methods: During a pilot school vaccination screening program in Zambia, GIS reference maps of health facility catchment areas were developed from hand-drawn sketch maps, catchment area shapefiles, and coordinates of prominent landmarks. These maps were iteratively refined with input from local health staff. In caregiver interviews, data collectors used the maps to identify the child’s zone of residence within the health facility catchment area. Vaccination status was extracted from paper registries used during screening. Geographic heat maps were generated in ArcGIS to visualize under-vaccination by zone. Results: Of 535 children screened across 25 zones, 29% were under-vaccinated. Under-vaccination varied by zone, with clusters of missed children identified, for example, 50% of children in Kabushi Zone 6 were under-vaccinated, compared with much lower rates elsewhere. Conclusions: Pairing school-based vaccination checks with GIS mapping offers a scalable approach to identifying missed communities in LMICs. This method enables spatial analysis without household visits, supporting targeted immunization planning where traditional data systems fall short. However, because the study was limited to children enrolled in five purposively selected schools, out-of-school children and those in other schools were not represented. This selection bias may underestimate the true extent of under-vaccination, and future evaluations should incorporate broader and more representative populations.

Malaria control is a public health priority but common control methods like indoor residual spraying and the use of bednets do not target outdoor-biting vectors. In settings with seasonal residual malaria transmission, we lack critical knowledge regarding anopheline species composition and their role in transmission. This study aimed to determine relative seasonal vector species abundance and associated household level factors in a low transmission setting in Choma District, Zambia. Indoor and outdoor adult vector collections were embedded in a community-based longitudinal cohort study in 60 households that were visited monthly for 2 years between 2018 and 2020. Surveys conducted at the time of trap placement collected information on animal ownership, housing structure, and the receipt of malaria interventions. Anopheline species identities were molecularly confirmed by polymerase chain reaction, and enzyme-linked immunosorbent assay was used to detect the circumsporozoite protein of Plasmodium falciparum. Generalized linear mixed effects negative binomial regression with zero-inflation models were used to describe the relationship between risk factors and the outcome of monthly anopheline counts at each household, stratified by season. The study collected 1,532 female anophelines, 76% of which were caught outdoors. The relative abundance differed by season: in the dry season, 90% of female anophelines were caught outdoors. Anopheles arabiensis was overall the most common vector, but made up only 28% of outdoor collections; the remainder were understudied anophelines including An. coustani, An. leesoni, An. rufipes, and An. squamosus. The only Plasmodium falciparum-infected mosquito was an An. squamosus that was caught outdoors. Owning more goats was associated with a 3.5 (IRR 4.47, 95% confidence interval [CI]: 2.00, 10.01) and 7.7 (IRR 8.73, 95% CI: 4.40, 17.32) times increase in indoor and outdoor anopheline collections in the dry season and a 1.2 (IRR 2.18, 95% CI: 1.12, 4.23) times higher risk of outdoor anophelines in the rainy season. Improved housing structure was associated with fewer indoor anophelines in the rainy season, but not during dry season or outdoor anopheline abundance any time of year. Vector control in this low transmission setting, therefore, needs to target anopheline mosquitoes year-round, must be expanded to target traditionally zoophillic mosquitoes, and leverage known risk factors when selecting methods of control.

Background:Mosquito species belonging to the Anopheles coustani group have been implicated in driving residual malaria transmission in sub-Saharan Africa and are regarded as an established primary vector in Madagascar. The morphological identification of mosquitoes in this group is challenging due to cryptic features and their molecular confirmation is difficult due to a paucity of reference sequence data representing all members of the group. Conventional molecular barcoding with the cytochrome oxidase I (COI) gene and the internal transcribed spacer 2 (ITS2) region targets is limited in their discrimination and conclusive identification of members of species complexes. In contrast, complete mitochondrial genomes (mitogenomes) have demonstrated much improved power over barcodes to be useful in rectifying taxonomic discrepancies in Culicidae. Methods:We utilized a genome skimming approach via shallow shotgun sequencing on individual mosquito specimens to generate sequence reads for mitogenome assembly. Bayesian inferred phylogenies and molecular dating estimations were perfomed on the concatenated protein coding genes using the Bayesian Evolutionary Analysis by Sampling Trees 2 (BEAST 2) platform. Divergence estimates were calibrated on published calucations for Anopheles-Aedes. Results:This study generated 17 new complete mitogenomes which were comprable to reference An. coustani mitogenomes in the GenBank repository by having 13 protein coding, 22 transfer RNA and 2 ribosomal RNA genes, with an average length of 15,400 bp and AT content of 78.3%. Bayesian inference using the concatenated protein coding genes from the generated and publicly available mitogenomes yielded six clades: one for each of the four taxa targeted in this study, the GenBank references, and a currently unknown species. Divergence times estimated that the An. coustani group separated from the An. gambiae complex approximately 110 million years ago (MYA), and members within the complex diverged at times points ranging from~34 MYA to as recent as ~7 MYA. Conclusions:These findings demonstrate the value of mitochondrial genomes in differentiating cryptic taxa and help to confirm morphological identities of An. coustani s.s., An. paludis, An. zeimanni and An. tenebrosus. Divergence estimates with the An. coustani group are similar to those for well-studied anopheline vector groups. These analyses also highlight the likely prescence of other cryptic An. coustani group members circulating in Zambia.

Benchmarks must be established and progress tracked to set a global target and take action.

Malaria is the greatest parasitic killer worldwide. Among the "big three" infectious diseases (HIV, tuberculosis, and malaria), malaria is unique for its eukaryotic biology and vector-borne transmission, features that contribute to its incessance. The history of malaria control is the archetype of infectious disease control. Infectious disease modeling, grounded in both theoretical constructs and empirical observations, places its origins in malaria, and the Global Malaria Eradication Program served as a template for smallpox and polio eradication. Once worldwide in its expanse, today malaria is a disease of rural poverty relegated to the tropics and subtropics, remaining a persistent challenge to public health.

BACKGROUND:Indoor residual spraying (IRS) is a malaria control strategy implemented before the rainy season. Nchelenge District, Zambia, is a holoendemic setting where IRS has been conducted since 2008 with little impact on malaria incidence or parasite prevalence. Pre-rainy season IRS may not reduce the post-rainy season peak abundance of the major vector Anopheles funestus. METHODS:A controlled, pretest-posttest, prospective cohort study assessed the impact of late-rainy season IRS on malaria prevalence, incidence, hazard, and vector abundance. A total of 382 individuals were enrolled across 4 household clusters, of which 2 were sprayed in April 2022 toward the end of the rainy season. Monthly household and individual surveys and indoor overnight vector collections were conducted through August 2022. Multivariate regression and time-to-event analyses estimated the impact of IRS on outcomes measured by rapid diagnostic tests, microscopy, and quantitative polymerase chain reaction. RESULTS:Among participants, 72% tested positive by rapid diagnostic test at least once, and incidence by microscopy was 3.4 infections per person-year. Residing in a household in a sprayed area was associated with a 52% reduction in infection hazard (hazards ratio, 0.48; 95% CI, .29-.78) but not with changes in incidence, prevalence, or vector abundance. The study-wide entomologic inoculation rate was 34 infectious bites per person per year. CONCLUSIONS:Monthly tracking of incidence and prevalence did not demonstrate meaningful changes in holoendemic transmission intensity. However, hazard of infection, which provides greater power for detecting changes in transmission, demonstrated that late-rainy season IRS reduced malaria risk.

Measles is one of the most contagious vaccine preventable diseases, causing severe complications and deaths globally. While vaccination with a measles-containing vaccine (MCV) has prevented millions of measles deaths, recent trends, especially from low- and middle-income countries, are discouraging. Measles cases have increased since 2021 as MCV coverage has decreased; and an estimated 107,500 measles deaths, mostly in children under-five years, occurred in 2023. Thus, a renewed focus on proven and innovative strategies to control measles is needed. The World Health Organization (WHO) recommends a first MCV dose administered at 9-15 months of age (routine MCV1), however MCV1 below 9 months of age (early MCV1) may increase vaccination coverage because uptake of all vaccines tends to be higher the younger the child, and this might protect vulnerable infants earlier in life. However, due to concerns about possible reduced vaccine performance, early MCV1 is not routinely recommended by WHO. WHO hosted an informal technical consultation on December 6-7, 2023, in Geneva, Switzerland to evaluate recent evidence on early MCV1 and identify evidence gaps for policy making. The recent evidence suggests a robust humoral immune response shortly after early MCV1 at 5-8 months of age. Immune blunting of a routine second MCV dose (e.g., MCV2) after early MCV1 was not demonstrated in the presented data. However, 3-7 years after MCV1, children receiving early MCV1 had lower measles antibodies than children receiving routine MCV1, suggesting faster waning of immunity. The totality of evidence on immune blunting remains inconsistent. Meeting participants thought more data are needed before revisiting WHO's current recommendation for a potential revision. Evidence gaps include: understanding measles disease burden and severity in infants; early MCV1 effectiveness and duration; vaccine-induced cellular immunogenicity; whether measles in infants is acquired from other infants or older children or adults; and blunting of routine MCV2. Addressing evidence gaps through targeted studies and measles outbreak investigations, as well as evaluations of country-level introductions of early MCV1 are warranted. Ensuring high MCV1 and MCV2 coverage remains the priority in measles control.

Community case management (CCM) combined with reactive test-and-treat (RTAT) for malaria was implemented by the National Malaria Elimination Program in a holoendemic region of Zambia. We assessed the impact of CCM + RTAT activities on malaria care seeking, health facility cases, and hospital mortality. We analyzed data from community surveys, a health facility-based passive surveillance network, and a hospital-based severe malaria surveillance system to compare metrics across the program eras (July 2016–July 2018, August 2018–October 2019, and November 2019–July 2021). Geospatial mapping was used to visualize trends in referrals and mortality. Clinical profiles of 696 hospitalized children with malaria were compared and in-hospital mortality were analyzed across periods using multiple logistic regression. There were more frequent health contacts for malaria reported by community members and a corresponding decrease in health facility malaria cases during CCM + RTAT. Pediatric patients admitted to the hospital with malaria during CCM + RTAT had less severe disease and shorter lengths of stay and in-hospital mortality was lower (odds ratio: 0.24, 95% CI: 0.07–0.84, P = 0.025). Geospatial mapping of the home villages of children hospitalized with malaria showed a wider catchment during CCM + RTAT than before or after. In this high malaria transmission setting, CCM + RTAT increased access to care, shifted malaria case burden from health facilities to community health workers, and improved in-hospital outcomes for malaria, likely from earlier referral. However, RTAT + CCM in this high-transmission area proved unsustainable because of excessive consumption of malaria commodities.

Increasing artemisinin partial resistance (ART-R) due to mutations in the gene encoding Kelch13 (Pfk13) protein in eastern Africa is of urgent concern, and mutations, such as Pfk13 P441L, continue to emerge. We used an amplicon deep-sequencing panel to estimate the prevalence of validated and candidate ART-R Pfk13 mutations in samples collected between 2018 and 2023 in southern Zambia. Pfk13 P441L was present in 30 of 501 samples (6%), and prevalence increased over time (0% to 7.2%). Further studies of the P441L mutation are needed to document its geographical origin, distribution and impact on treatment outcomes.

Eleven countries have been certified as malaria free since 2016, but none of these are in subSaharan Africa where elimination challenges are unique. The 1-3-7 focus investigation approach is an implementation strategy that requires case reporting, case investigation/classification, and focal classification/response to be completed one, three, and seven days, respectively, after index case diagnosis. Real-time short-messaging-service reports are sent at each step to add accountability and data transparency. Reactive case detection is one focal response of the 1-3-7 strategy. China, Thailand, Myanmar, and other countries cite high fidelity to deadlines and broad acceptability of 1-3-7, but this strategy has yet to be widely deployed in Africa. This mixed-methods study evaluated implementation and service outcomes of 1-3-7 focus investigation in a rural area of southern Zambia. Selected outcomes were fidelity, efficiency, feasibility, equity, and acceptability, assessed via program metadata and semi-structured interviews with program personnel. Fidelity was moderate with 61% of cases reported. Focus investigation and reactive case detection completion doubled in areas using 1-3-7, from 20% to 42%. However, reactive case detection, which involved screening community members residing within 140 meter of index cases with a rapid diagnostic test, detected few parasitemic individuals, suggesting this may not be the most efficient day 7 response in this setting. Mobile phone network coverage was a common challenge to feasibility that likely affected reporting rates and fidelity. Thirty-four percent of health-facility diagnosed cases were not eligible for 1-3-7 follow-up. Distance from the health center was a barrier to feasibility and equitable reach of services. Reporting was faster in areas where health workers classified transmission as higher and slower in areas with poor mobile phone network coverage. The strategy was widely accepted. Scale-up should include adherence-focused management strategies, spatially targeted interventions not reliant on RDTs, and complementary surveillance that targets hard-to-reach populations.

Mutare city of Zimbabwe was considered free of autochthonous malaria, until 2017, when the Ministry of Health and Child Care formally confirmed escalating cases of locally transmitted malaria in the city. The current study examined the risk factors for malaria cases in the city to aid in formulation of targeted intervention packages for helping restore malaria-free status. The study employed complementary cross-sectional and case–control designs to ascertain the magnitude and risk factors of urban malaria cases presenting at all eight primary health care facilities of Mutare city from 2022 to 2023. Malaria cases were enrolled as confirmed by RDT or microscopy on presenting all-age symptomatic suspected malaria patients. Controls were similarly enrolled as all-age symptomatic suspected malaria patients found negative by both RDT and microscopy. All cases and controls were enrolled as representative of the presenting population with no matching. Data were analysed for descriptive and prevalence statistics, as well as risk factors, using SPSS Faculty version 27. In a multivariate binary logistic model, significant risk factors for malaria cases found in the city included residential locale (RR [95

Models of measles transmission can be used to identify areas of high risk to tailor immunization strategies. Estimates of spatial connectivity can be derived from data such as mobile phone records, but it is not clear how this maps to the movement of children who are more likely to be infected. Using travel surveys across 2 districts in Zambia and national mobile phone data, we compared estimates of out-of-district travel for the population captured in the mobile phone data and child-specific travel from travel surveys. We then evaluated the impact of unadjusted and adjusted connectivity measures on simulated measles virus introduction events across Zambia. The number of trips made by children from the travel survey was 3 to 5 times lower than the general population estimates from mobile phone data. This decreased the percentage of districts with measles virus introduction events from 78% when using unadjusted data to 51% to 64% following adjustment. Failure to account for age-specific heterogeneities in travel estimated from mobile phone data resulted in overestimating subnational areas at high risk of introduction events, which could divert mitigation efforts to districts that are at lower risk.

Background:Resistance to antimalarial drugs remains a major obstacle to malaria elimination. Multiplexed, targeted amplicon sequencing is being adopted for surveilling resistance and dissecting the genetics of complex malaria infections. Moreover, genotyping of parasites and detection of molecular markers drug resistance in resource-limited regions requires open-source protocols for processing samples, using accessible reagents, and rapid methods for processing numerous samples including pooled sequencing. Methods:P lasmodium f alciparum Streamlined Multiplex Antimalarial Resistance and Relatedness Testing (Pf-SMARRT) is a PCR-based amplicon panel consisting of 15 amplicons targeting antimalarial resistance mutations and 9 amplicons targeting hypervariable regions. This assay uses oligonucleotide primers in two pools and a non-proprietary library and barcoding approach. Results:We evaluated Pf-SMARRT using control mocked dried blood spots (DBS) at varying levels of parasitemia and a mixture of 3D7 and Dd2 strains at known frequencies, showing the ability to genotype at low parasite density and recall within-sample allele frequencies. We then piloted Pf-SMARRT to genotype 100 parasite isolates collected from uncomplicated malaria cases at three health facilities in Dschang, Western Cameroon. Antimalarial resistance genotyping showed high levels of sulfadoxine-pyrimethamine resistance mutations, including 31% prevalence of the DHPS A613S mutation. No K13 candidate or validated artemisinin partial resistance mutations were detected, but one low-level non-synonymous change was observed. Pf-SMARRT's hypervariable targets, used to assess complexity of infections and parasite diversity and relatedness, showed similar levels and patterns compared to molecular inversion probe (MIP) sequencing. While there was strong concordance of antimalarial resistance mutations between individual samples and pools, low-frequency variants in the pooled samples were often missed. Conclusion:Overall, Pf-SMARRT is a robust tool for assessing parasite relatedness and antimalarial drug resistance markers from both individual and pooled samples. Control samples support that accurate genotyping as low as 1 parasite per microliter is routinely possible.