Plasmodium falciparum infection (MOI) is related to pregnancy outcomes, is of interest in sub-Saharan area where malaria is highly endemic. The present study aimed to characterize the genetic diversity of P. falciparum in women at delivery from Southern Brazzaville, and investigate whether the MOI is associated with maternal anaemia, preterm delivery, or low birth weight.Investigating whether the multiplicity of P. falciparum microscopic and submicroscopic parasitaemia, and parasite DNA genotyping by nested PCR.This was a cross sectional study carried out with samples collected between March 2014 and April 2015 from 371 women recruited at delivery at a Health Centre in southern Brazzaville, Republic of Congo. Matched peripheral, placental, and cord blood collected from each of the women at delivery were used for the detection of msp-1 block 2 family allelic types  were observed in all the three compartments of blood, with K1 being most abundant. K1  and MAD20  were more diverse compared to RO33 . From the 250 women with microscopic and/or submicroscopic parasitaemia, 38.5%, 30.5%, and 18.4% of peripheral, placental and cord blood sample, respectively, harboured more than one parasite clone, and polyclonal infection was more prevalent in the peripheral blood of women with microscopic parasitaemia (54.5%) compared to those with submicroscopic parasitaemia (36.7%) (p = 0.02). The mean multiplicity of genotypes per microscopic and submicroscopic infection in peripheral blood was higher in anemic women  than in non-anaemic women  (p = 0.03 and 0.06). In logistic regression, women infected with four or more clones of the parasite were 9.4 times more likely to be anaemic than women harbouring one clone. This association, however, was only observed with the peripheral blood infection. No significant association was found between the MOI and low birth weight or preterm delivery.From 371 recruited women, 27 were positive to microscopic malaria parasitaemia while 223 women harboured submicroscopic parasitaemia. All P. falciparum is high in pregnant women from southern Brazzaville in the Republic of Congo, and the multiplicity of the infection might represent a risk for maternal anaemia.These results indicate that the genetic diversity of  Plasmodium falciparum, the deadliest malaria parasite globally [Plasmodium biology and host-parasite interactions.Pregnancy associated malaria (PAM) remains a major public health problem in sub-Saharan Africa, where approximately 50 million women become pregnant each year, and are at high risk of exposure to globally . A signiglobally . Howeverglobally , which wP. falciparum to evade the immune response in pregnant women involves the sequestration of the parasite infected red blood cells in the placental tissue [P. falciparum infected erythrocytes variant surface protein, and the most promising target for vaccine development against PAM [Plasmodium antigens mediated immune response also contribute to the malaria parasite clearance in pregnant women [P. falciparum antigens, which limits the efficacy of acquired protective immunity against specific malaria parasite antigens [P. falciparum strains [P. falciparum blood-stage antigens, MSP-1 is the most expressed protein, and it also documented as a suitable markers to discriminate subpopulations of P. falciparum [msp-1 gene located on chromosome 9, which contains 17 blocks of sequences flanked by conserved regions [msp-1, is grouped under three allelic families of K1, MAD20 and RO33 [P. falciparum msp-1 has commonly been used as a molecular marker in studies of malaria transmission dynamics and host immunity in P. falciparum malaria [One of the most important strategies used by l tissue , 3. The l tissue . Althougnt women . This suantigens . In addiantigens . Merozoi strains . Among tlciparum . It is e regions  and has  regions . Block 2and RO33 . Fragmen malaria –16.Plasmodium diversity and MOI in non-pregnant individuals [P. falciparum in Congolese pregnant women [P. falciparum genetic diversity, this study aimed to characterize the genetic diversity of P. falciparum by investigating msp1 block 2 polymorphisms, and determine whether the multiplicity of the infection is associated with poor pregnancy outcomes in women from Southern Brazzaville in the Republic of Congo.In the areas of high malaria transmission, there is an increase of ividuals , 17. In ividuals , 19, whiividuals , 21. Hownt women , and nonP. falciparum as the predominant malaria parasite and Anopheles gambiae as the main mosquito vector.This descriptive cross-sectional study was carried out from March 2014 to April 2015 at the Madibou integrated health centre, situated in the southern part of Brazzaville, in the Republic of Congo. The capital, Brazzaville, is located along the Congo River, in the south of the country. Since the country is located on the Equator, the climate is consistently humid year-round, with the average day temperature of 25 °C, and at night between 16 and 21 °C. The average yearly rainfall ranges from 1100 mm in the south to over 2000 mm in the central and north parts of the country. The rainy season which lasts 9 months, has two rainfall maxima: one in March–May and another in September–November. The malaria transmission in Brazzaville is perennial with A total of 371women aged 16 to 39 years old with no history of clinical malaria in the last two weeks before the delivery, and no history of fever, 48 h before the delivery or at the time of sample collection, were randomly recruited. Information on the mother’s health, estimated length of pregnancy, parity, age, baby birth weight, usage of anti-malarial drugs, IPTp-SP usage, and bed nets usage, were recorded using a standard questionnaire. The poor pregnancy outcomes investigated included preterm delivery , low birth weight (birth weight <2.5 kg) and maternal anaemia (haemoglobin level ˂11 g/dL). Peripheral, placental and cord blood samples were collected in EDTA tubes from women immediately following delivery as previously described , 24. A pThick and thin blood smears were prepared for each peripheral and cord blood sample using Giemsa-Wright stain and read by two skilled microscopists to determine the presence or not of malaria parasites and the parasitaemia. Haemoglobin levels in maternal peripheral blood were determined using a haematologic analyzer.msp-1, considered to be the most informative genetic marker for the assessment of multiplicity of P. falciparum infection [P. falciparum laboratory strain 3D7) and DNA-free negative controls were included in each series of reactions. Five microlitres of each of the PCR products were loaded on to a 1.5% agarose gel, stained with Syber Green, separated by electrophoresis and visualized under UV light , and fragment sizes estimated by comparison to DNA ladder. The prevalence of each allelic type was determined as the presence of PCR products for the type in the total number of amplified bands. The MOI, the number of genotypes per infection was estimated as the average number of PCR fragments per individual, by dividing the total number of msp-1 fragments detected by the number of positive samples as described previously [msp-1 types in the sample while isolates with two or more genotype were considered as polyclonal infection [Parasite genomic DNA was extracted from collected blood samples using the QIAmp DNA mini kit according to manufacturer’s instructions . Briefly, 200 µL of the whole blood was used to yield a nucleic acid elution volume of 60 µL and kept at − 20 °C until genotyping. Nested PCR genotyping was performed by amplification of the highly polymorphic Block 2 region of nfection . An initeviously . Monoclonfection .Table 1PGraph Pad Prism (version 6.0.1) and XLSTAT (version 2011.2.08) software were used for the statistical analyses. Continuous variables  are reported as means ± standard deviations (SD) or medians with interquartile range (IQR). Differences between groups were compared using unpaired Student’s t test for normally distributed continuous data while Mann–Whitney Rank Sum test or Kruskal–Wallis test was used for non-normal distributed continuous data. Categorical variables  were reported as percentages and were compared using Fisher’s exact test or Chi Square test. Logistic regression analyses were performed where preterm delivery, low birth weight, maternal anaemia were entered in the model as dependent variables and the infection with 1clone, 2–3 clones, and ≥ 4 clones as independent variables. The polyclonal infection status  was also entered in the models as dependent variable when mother age, gravidity, using bed net and IPT-SP were entered as independent variables. Two-sided p values ˂ 0.05 were considered statistically significant.P. falciparum genetic diversity. No case of microscopic infection was detected in the cord blood, and 22 (81.5%) women had microscopic parasitaemia in both peripheral and placental blood. Of 223 women with submicroscopic parasitaemia, 68 (30.5%) women were positive for both peripheral and placental blood while only 27 (12.1%) women were positive for all the three blood compartments. Women with microscopic malaria parasitaemia  were younger than those with submicroscopic parasitaemia  (p = 0.027). The mean parity (2.1) and gravidity (2.2) were lower (p = 0.05 and 0.008 respectively) in women with microscopic parasitaemia than in submicroscopic parasitaemia positive women (2.7 and 3.2 respectively). Maternal median haemoglobin level was lower in women with microscopic parasitaemia (10.05 g/dL) than in submicroscopic parasitaemia positive group (11.60 g/dL) (p = 0.011), and the percentage of anaemia was higher in the group of women harbouring microscopic parasitaemia (p = 0.02). The mean birth weight as well as the frequency of preterm delivery were not significantly different between women with microscopic  and submicroscopic parasitaemia , respectively . The mean number of IPTp-SP doses taken by submicroscopic parasitaemia positive women was higher than that of microscopic parasitaemia positive women (p = 0.01), but the proportion of women using bed nets was greater in microscopic parasitaemia positive women compared to submicroscopic parasitaemia group (p < 0.0001).The characteristics of the study participants are summarized on Table P. falciparum field isolates. The number of genotypes observed at each blood compartment is shown in Fig. msp1 family specific allelic types i.e. K1, MAD 20 and RO33 were observed in the different blood compartment. The gene was more diverse in the peripheral blood where twenty eight (28) different alleles were observed, representing K1 , MAD20  and RO33 , than in the placental blood with 25 different alleles, representing K1 , MAD20 , R033 , and in cord blood with 19 alleles, K1 , MAD20 , R033 . In the peripheral blood compartment, 171 (51%) individuals harboured K1 type allele compared to 76 (22%) for MAD20 and 91 (27%) for RO33 type allele. The similar trend was observed in the placental blood compartment where 70 (49%) individuals harboured K1 type allele compared to 37 individuals (26%) for MAD20, and 35 (25%) individuals for RO33 type allele; and in cord blood compartment where 29 (50%) individuals harboured K1 type allele compared to 14 individuals (24%) for MAD20, and 15 (26%) individuals for RO33 type allele.Length polymorphism was assessed in 250 msp-1 bloc 2 family alleles in paucigravid (1or 2 gravities) and multigravid (more than two gravidities) women are presented on Fig. The frequency distribution of the msp1 bloc 2 family alleles was less diverse in microscopic parasitaemia positive women compared to submicroscopic parasitaemia positive contreparts: K1 , MAD20 , and RO33  for the peripheral blood compartment; K1 , MAD20 , and RO33 (3 vs. 6 Alleles) for placental blood compartment  was 9.4 (95% CI = 1.1–82.5), compared to 0.3 (95% CI = 0.3–8.9) for placental blood infection, and 1.8 (95% CI = 0.3–8.9) for cord blood infection. The odds ratio for preterm delivery and low birth weight did not significantly change with increased number of parasite clones per infection  as the intermittent preventive treatment (IPT) strategy during pregnancy . Patientmsp-1 block 2 family allelic types  were observed in all the three compartments of blood, with K1 being most abundant followed by MAD20. Studies in other malaria endemic countries including neighbouring Gabon [P. falciparum [The results of this study indicate that ng Gabon , Nigeriang Gabon  as well ng Gabon  and Inding Gabon  have conng Gabon , 27. In ng Gabon , 33. Howlciparum –36.P. falciparum observed in the current study is indicative of high transmission of malaria infection in the area and suggest a great potential for the development of resistance to SP which may render it less effective as a preventive treatment. Otherwise, although some authors believe that high biodiversity of malaria parasite might be benefit for the naturally acquired immunity to malaria since it gives the chance to subjects to be exposed to several different malaria antigens strains, the extension of the genetic diversity of P. falciparum antigens limits the efficacy of acquired protective immunity to a specific malaria candidate vaccine [P. falciparum might also compromise the success of an anti-malarial vaccine implementation in this study area.The highly diverse nature of  vaccine . Thus, tmsp1 type genes were more diverse in peripheral blood compared to placental and cord blood. This data are different from those reported in Sudanese women, showing higher diversity of the gene in the placental blood compartment [P. falciparum strains circulating in the peripheral blood of pregnant women might differ from that found in the placental and cord blood. Previous studies from high malaria transmission settings have reported several strains of P. falciparum circulating in pregnant women among which some were more prevalent in the placental blood in comparison to peripheral blood compartment. The difference observed between the current study and the report [msp1 gene diversity between the different bloods compartments might be due to the difference in P. falciparum strains circulating in Sudan in comparison with the parasite strains in circulation in the Republic of Congo.The partment , but cone report  on the vmsp1 family alleles in this study were more diverse in submicroscopic parasitaemia positive women, but more frequent in microscopic parasitaemia positive women. This results are in line with previous findings suggesting that high diversity of P. falciparum increases the naturally acquired antibody repertory which might reduce the level of parasitaemia [Conversely to some of previous reports that did not find any association between malaria parasite density and its genetic diversity , 38, thesitaemia . These fP. falciparum strains. This corroborate the findings of this study showing lower risk of microscopic infection in older women, with high number of gravidity compared to younger women with low gravidity. Accurate detection of microscopic P. falciparum infection remains a major challenge in pregnant women who commonly harbour low parasitaemia, likely due to ITP-SP usage which reduces the parasite replication, and to ability of parasite to sequester in the placental tissue. These observations might also explain the high prevalence of submicroscopic parasitaemia (60.1%) found in the present study. Nevertheless, it is commonly known that the detection cut-off of malaria parasite by microscopic examination of Giemsa-stained thick blood film significantly varies with microscopists, and the rate of missed detection increases with low parasitaemia infection.However, the higher frequency of the alleles observed in the microscopic parasitaemia positive women in comparison with women harbouring submicroscopic parasitaemia was unexpected, and may be explained by the high parasite density in the first group that eases its detection. Subsequent pregnancies in high malaria transmission settings are associated with high exposure to PAM which increases the naturally acquired antibody mediated immunity against PAM- specific P. falciparum infection are at high risk of suffering microscopic parasitaemia malaria infection. The analysis of the relationship between the biodiversity of P. falciparum in women and poor pregnancy outcomes, showed that maternal anaemia was more prevalent in women with high MOI. No significant association was found between the parasites MOI and preterm delivery or low birth weight. In addition, SP or insecticide treated bed nets (ITNs) usage as well as mother age and gravidity had no significant influence on the msp1 genes diversity in the current study, in contrast to a previous study carried out in Sudan, which reported significant higher multiplicity of infection identified by at least two alleles of msp-1 among paucigravidae compared to multigravidae [The frequency of polyclonal infection in the peripheral blood was higher in women with microscopic parasitaemia (54.5%) compared to those with submicroscopic parasitaemia (36.7%). These findings suggest that pregnant women having polyclonal gravidae . The maiP. falciparum is high in pregnant women from southern Brazzaville of the Republic of Congo, and the MOI might represent a risk for maternal anaemia.These results indicate that the genetic diversity of


There has been a global decline in malaria transmission over the past decade. However, not much is known of the impact of this observation on the burden of malaria infection in pregnancy in endemic regions including Ghana. A narrative review was undertaken to help describe trends in malaria infection in pregnancy in Ghana. Among others, such information is important in showing any progress made in malaria in pregnancy control.Plasmodium falciparum infection in pregnancy was conducted.To describe trends in pregnancy-associated malaria infection in Ghana, a search and review of literature reporting data on the prevalence of asymptomatic Thirty-six (36) studies, conducted over 1994–2019, were included in the review. In the northern savannah zone with largely seasonal malaria transmission, prevalence appeared to reduce from about 50–60% in 1994–2010 to 13–26% by 2019. In the middle transitional/forest zone, where transmission is perennial with peaks in the rainy season, prevalence apparently reduced from 60% in the late 1990 s to about 5–20% by 2018. In the coastal savannah area, there was apparent reduction from 28 to 35% in 2003–2010 to 5–11% by 2018–2019. The burden of malaria infection in pregnancy continues to be highest among teenagers and younger-aged pregnant women and paucigravidae.There appears to be a decline in asymptomatic parasite prevalence in pregnancy in Ghana though this has not been uniform across the different transmission zones. The greatest declines were noticeably in urban settings. Submicroscopic parasitaemia remains a challenge for control efforts. Further studies are needed to evaluate the impact of the reduced parasite prevalence on maternal anaemia and low birthweight and to assess the local burden of submicroscopic parasitaemia in relation to pregnancy outcomes.The online version contains supplementary material available at 10.1186/s12936-021-04031-3. Plasmodium falciparum infection accounts for the greater burden of morbidity and mortality though Plasmodium vivax may also be important in Southeast Asia and South America [Malaria in pregnancy (MIP) remains a public health burden in endemic areas. Adverse outcomes include maternal anaemia and mortality, fetal growth restriction, abortion, preterm delivery and low birthweight following parasite placental sequestration and subsequent immunological processes –4. Plasm America , 6. Over America .Insecticide-treated bed nets (ITNs) and intermittent preventive treatment with sulfadoxine–pyrimethamine (IPTp-SP) are the key preventive interventions in endemic areas with stable transmission. Use of ITNs has been reported to underlie a 23% reduction in placental parasitaemia in a systematic review while ≥ 3 doses of IPTp-SP has been associated with up to 56% reduction in the risk of peripheral parasitaemia and a significant reduction in submicroscopic infections –10.P. falciparum parasitaemia in pregnant women in Ghana and other endemic areas in spite of their vulnerability to malaria. Such data is important to help evaluate, directly or indirectly, the effectiveness of many years of targeted preventive interventions including IPTp-SP and ITNs. It will also be useful to identify where greater burdens persist for intensification of control interventions.In Ghana, MIP accounted for 17.6% of outpatient department attendance, 13.7% of hospital admissions among pregnant women and 3.4% of maternal deaths in 2014 with the first two indicators declining to 14% and 11% in 2015 . There hThis narrative review seeks to describe trends in asymptomatic parasitaemia prevalence among pregnant women in the three malaria ecological zones in Ghana; namely the northern savannah zone characterized by intense and seasonal transmission , the transitional savannah/forest zone in the middle belt of the country with perennial and intense transmission and the coastal savannah belt  see Fig.P. falciparum infection in Ghanaian pregnant women, a search was conducted in Google Scholar and PubMed using the terms  AND prevalence AND Ghana. The literature search was conducted from January to March, 2021 and was not restricted to any particular year or period of publication. Studies were included in the review if they reported prevalence of asymptomatic P. falciparum parasitaemia in women in Ghana anytime during pregnancy or at delivery and at any time of the year, if they were primary studies and also if they reported the period of data/sample collection. Titles/abstracts were screened and those deemed relevant were retrieved and further assessed for eligibility after checks for duplication. Data on parasite prevalence, method of detection, period over which study was conducted and whether peripheral/placental blood or placental biopsy was used were extracted from the included studies using a predesigned data extraction sheet. Parasite prevalence was compared over the years to describe trends.To identify studies reporting prevalence of asymptomatic Supporting data on malaria test positivity rates  among pregnant women was sourced from the district health information management system (DHIMS 2) database. The DHIMS 2 is an electronic database employed by the Ghana Health Service for reporting disease morbidity and mortality and receives monthly inputs from health facilities across the country. Suspected and parasitologically-confirmed MIP cases for Greater Accra, Ashanti and the former Northern region  over a 7-year period 2014–2020) were available to the authors and used to calculate test positivity rates for the respective years. The listed regions were chosen to represent the three malaria transmission settings  ranged about 50–60% in the 17-year period from 1994 to 2011 with a number of the studies conducted during that time reporting closer to 60% [Asymptomatic r to 60% –16. Subsr to 60% . This der to 60% .P. falciparum infection during pregnancy was generally around 20–28% as detected by peripheral blood film microscopy mostly [No report of the prevalence of pregnancy-associated malaria infection was found for this zone prior to 2003. In 2003/2004, over a third of women (35.7%) in a study in rural Accra had placental blood parasitaemia on microscopy . Over thy mostly –25 with y mostly .Comparatively, between 2011 and 2019, the prevalence reduced and has ranged between 10 and 17% –32 thougStudies conducted between 1998 and 2006 in the Ashanti Region reported prevalence of asymptomatic malaria infections during pregnancy around 35% by microscopy , 37 whilIn the northern part of this zone  from 2014 to 2020 with Greater Accra region showing the greatest decline of 74% followed by Ashanti and the former Northern region  were more likely to have parasitaemia or higher parasite densities compared to those above 25–30 years old , 45. In Similarly, primi- and secundigravidae had higher odds of parasitaemia and higher parasite densities compared to multigravidae and this was true for both peripheral and placental parasitaemia , 45, 47.The effect of gestation on maternal parasitaemia appeared to be variable. Pregnant women in the third trimester had less likelihood of parasitaemia and high parasite densities compared to those in the earlier stages of pregnancy in the northern savannah zone , but othThe effect of bed net use on maternal parasitaemia was also variable. Some studies reported no association between bed net use and parasitaemia , 33 whilPrevalence of malaria infection in Ghanaian pregnant women, from 1994 to 2019, showed apparent decline across all transmission zones. In the northern savannah zone, the prevalence reduced from about 50–60% over 1994–2010 , 15 to aP. falciparum parasite prevalence from 25.5 to 14.1% between 2011 and 2019 [The apparent decline in asymptomatic parasitaemia prevalence among pregnant women mirrors reported reductions in all-age out-patient malaria cases in Ghana by 57%, under-five malaria admissions and mortality by 46% and 70% respectively between 2005 and 2010 and mid-2015  and falland 2019 –52. ThisData from current malaria transmission studies in Ghana is lacking but a decline in entomological inoculation rate from about 400 to 139 infective bites/person/year between the early 2000 s and 2014/2015 in the northern zone has been reported . This maThe prevalence of maternal parasitaemia appears to remain relatively higher in the northern savannah transmission zone in spite of the seeming general decline described and this may have to do with the characteristic seasonal malaria transmission pattern, the hot weather that may deter consistent bed net utilization and possibly slower urbanized development compared to Accra in the coastal belt , 56. It In Greater Accra , the apparent decline in placental malaria infection prevalence from about 36% to under 1% between 2003/2004 and 2015–2017 , 34 coulInterestingly, two studies conducted in 2018 and 2019 in urban and rural parts of Greater Accra region respectively reported an approximately equal prevalence of about 11% for peripheral parasitaemia , 32. ThiIn spite of the generally low prevalence reported in Greater Accra, it must be noted that PCR methods have reported higher prevalence of about 13% and 43% for placental and peripheral parasitaemia respectively even in urban communities . Being mDespite the general decline in parasitaemia in pregnant women, primigravidae, secundigravidae and younger aged women remain most susceptible to infection and this agrees with previous observations elsewhere , 65, 57.Vaccines to prevent pregnancy-associated malaria is also another option. As the search for an effective candidate continues , such vaTest positivity rates over 2014–2018 in Ashanti and the former Northern regions, respectively averaging 33% and 46% per year, were appreciably higher than asymptomatic infection prevalence rates observed over the same period. Pregnant women tested in the health facilities are often symptomatic and apparently have higher parasite densities. Asymptomatic malaria infections are less likely to be detected with the conventional light microscopy and rapid diagnostic tests often due to lower densities . The potThe declining trend of malaria infection in pregnancy seems to mirror apparent increments in access to and use of ITNs and IPTp-SP and is consistent with previous reports , 10. TarSimilarly, bed net utilization has also improved over the years , 72 but In spite of the recent successes, ITN coverage has been less than optimal and ownership has been plagued by health system challenges including frequent stock-outs . KnowledSimilar to ITN ownership and use, coverage of three or more doses of SP for IPTp in Ghana, per current WHO recommendation , has incAlthough of contextual value only to this review which focused on asymptomatic parasitaemia prevalence from field studies, using DHIMS 2 data for only 5 out of 16 regions gives a restricted view of MIP test positivity rates in Ghana and is a limitation. Secondly, the contribution of changing rainfall and temperature patterns, over the review period, was not assessed. The findings, however, are relevant and draw attention to gains made and weaknesses that need to be addressed to consolidate and improve the gains. It must be remembered that Ghana is part of the high burden high impact countries for malaria and the findings are important to help reduce the malaria burden, especially in pregnant women.There has been an appreciable decline in malaria parasite prevalence in Ghanaian pregnant women over the last 25 years similar to trends observed in children under-five in Ghana and globally. This development appears to be aligned with increased access to ITNs and uptake of at least 3 doses of IPTp-SP. The greatest declines appear to be in urban areas and reinforce known disparities between rural and urban parasite burdens. Despite this decline, submicroscopic parasitaemia remains a risk and together with asymptomatic parasitaemia, pose challenges for reducing transmission as part of control efforts. Larger-scale assessments of the local burden of submicroscopic parasitaemia and how they relate to pregnancy outcomes are needed. Additionally, further studies are needed to assess the impact of the observed reduction in asymptomatic malaria parasite prevalence in Ghanaian pregnant women on the burden/trends in maternal anaemia, low birthweight, stillbirth and other adverse outcomes of MIP.Additional file 1: Table S1. Numbers of pregnant women with malaria from 2014 to 2020 in Ashanti Region, Greater Accra and the former Northern Regions.


Plasmodium falciparum infections in malaria-endemic regions of Myanmar.Screening malaria-specific antibody responses on protein microarrays can help identify immune factors that mediate protection against malaria infection, disease, and transmission, as well as markers of past exposure to both malaria parasites and mosquito vectors. Most malaria protein microarray work has used serum as the sample matrix, requiring prompt laboratory processing and a continuous cold chain, thus limiting applications in remote locations. Dried blood spots (DBS) pose minimal biohazard, do not require immediate laboratory processing, and are stable at room temperature for transport, making them potentially superior alternatives to serum. The goals of this study were to assess the viability of DBS as a source for antibody profiling and to use DBS to identify serological signatures of low-density P. falciparum antigen fragments. Signal and trends in both sample matrices were compared. A case-control study was then performed using banked DBS samples from malaria-endemic regions of Myanmar, and a regularized logistic regression model was used to identify antibody signatures of ultrasensitive PCR-positive P. falciparum infections.Matched DBS and serum samples from a cross-sectional study in Ingapu Township, Myanmar were probed on protein microarrays populated with P. falciparum infection, albeit with modest diagnostic characteristics .Approximately 30% of serum IgG activity was recovered from DBS. Despite this loss of antibody activity, antigen and population trends were well-matched between the two sample matrices. Responses to 18 protein fragments were associated with the odds of asymptomatic Malaria-specific antibody responses can be reliably detected, quantified, and analysed from DBS, opening the door to serological studies in populations where serum collection, transport, and storage would otherwise be impossible. While test characteristics of antibody signatures were insufficient for individual diagnosis, serological testing may be useful for identifying exposure to asymptomatic, low-density malaria infections, particularly if sero-surveillance strategies target individuals with low previous exposure as sentinels for population exposure.The online version contains supplementary material available at 10.1186/s12936-021-03915-8. Over the last decade, Myanmar, the country in the Greater Mekong Subregion that historically has had the highest burden of malaria, has made considerable progress toward malaria elimination. Since 2010, the number of malaria cases in Myanmar has decreased by more than 94% , 4 as weAntibody biomarkers represent promising tools for malaria surveillance in elimination settings that may mitigate some of the challenges of measuring parasite prevalence with usPCR. Antibody responses can reveal past exposure in addition to current infection status, adding substantially more information to population-level measures of transmission , 14. AntPlasmodium falciparum 3D7 reference genome (Pf250) [P. falciparum malaria infections.Protein microarrays are useful for screening antibody responses against large panels of antigens and protein fragments to identify potential biomarkers of exposure. In this format, antigens are printed onto nitrocellulose pads, antibodies in samples bind to antigens, and fluorescently-labelled secondary antibodies enable quantitative readout of signal. Protein microarrays have been used extensively to screen malaria-specific antibody responses, including those that elicit protection from uncomplicated and severe disease –20 and t (Pf250) . It was  (Pf250) , may eliP. falciparum infections and 5.6% Plasmodium vivax infections during the rainy season in 2015 [A cross-sectional study was conducted in Ingapu Township, Myanmar, during the rainy season in August 2018. This region was previously characterized by the Myanmar National Malaria Control Programme as a medium-transmission area, with reported usPCR prevalence of 8.7%  in 2015 . A studyP. falciparum by usPCR, and controls (n = 175) were individuals who tested negative for P. falciparum by usPCR. This study was designed specifically to identify antibody markers of usPCR+ P. falciparum malaria infections, so individuals with P. vivax mixed and mono-infections were included in the case and control groups, respectively, to account for potential cross-reactive responses. The case group included 25 individuals with mixed P. falciparum and P. vivax infections. The control group included 25 individuals who were P. vivax-positive.To identify potential markers of asymptomatic usPCR+ malaria infections, a retrospective case-control study nested within a previously reported 2015 cross-sectional survey  in whichFor the study comparing antibody responses from DBS and serum samples, capillary whole blood was collected by finger prick. Each individual was screened for malaria by RDT (SD Bioline Ag Pf/Pv). DBS samples  were collected on Whatman 3MM chromatography paper (WHA3030861) for usPCR analysis as previously described  and ProtP. falciparum and P. vivax infections by usPCR, which targets the parasite 18S rRNA gene and transcripts. Human actin DNA was used as an internal extraction control. Extraction and reverse transcription PCR (RT-PCR) were performed as previously described [P. falciparum and 49.5 copies/µL of 18 S rRNA for P. vivax [All samples were tested for escribed . Brieflyescribed . All datP. vivax .Protein Saver 903 DBS samples were punched with a 6.35 mm hole punch (Staples 10573-CC) into 2-mL microcentrifuge tubes. Next, 150 µL Pierce Casein Blocking Buffer in PBS (Thermo Scientific 37528) with 0.3% Tween-20 was added to each tube, and samples were incubated overnight with gentle rocking at 4 °C. The following morning, DBS were removed and discarded, and 150 µL glycerol was added to stabilize the remaining supernatant. Eluates were stored at − 20 °C.P. falciparum (strain 3D7) were cloned and expressed in individual T7 Escherichia coli-derived in vitro transcription/translation (IVTT) reactions (GenScript). Reaction products, along with no-template IVTT control reaction mixtures, were printed directly onto nitrocellulose pads on glass slides (GraceBio).Microarrays were constructed as previously described . BrieflyE. coli lysate (GenScript) in GVS FAST Blocking Buffer (#10485356) and incubated at room temperature for 30 min. DBS eluates (150 µL) were combined with 50 µL 80% E. coli lysate in GVS Fast Blocking buffer for 30 min at room temperature. This dilution of DBS eluates approximates a 1:100 serum dilution. Matched DBS and serum samples were probed on the same slides to avoid batch effects. For the case-control study, malaria cases and controls were randomized on the microarray slides prior to probing to avoid batch effects. Protein microarrays were assembled into GraceBio Proplates (#246890), and the nitrocellulose microarray pads were rehydrated with 100 µL GVS FAST Blocking buffer for 30 min on an orbital shaker. Supernatants were aspirated before 100 µL of prepared DBS or serum samples were added to the pads. Samples were incubated on the protein arrays at 4 °C overnight with gentle rocking. The following morning, supernatants were aspirated and washed quickly 3× with TRIS Buffered Saline with 0.05% Tween-20 (TTBS) followed by 35-min TTBS washes on an orbital shaker. Biotin-conjugated goat anti-human IgG secondary antibody  was diluted 1:400 and incubated on the pads (100 µL) for 1 h at room temperature on an orbital shaker. Pads were washed with TTBS as described above, and 100 µL of streptavidin-coated quantum dots  at 1:200 dilution in GVS FAST Blocking buffer was added to each pad and incubated for 1 h on an orbital shaker. Finally, microarrays were washed with TTBS as described above, rinsed in DI water, and air-dried by centrifugation for 5 min (1000g). Fluorescence intensities were measured using an ArrayCAM Imaging System from Grace BioLabs .Pf250 protein microarrays were probed as previously described . Serum sAll analyses were performed in the R environment (version 3.6.1) or GraphPad Prism version 8.1. The average fluorescence intensity of the no-template control spots for a sample was subtracted from all fluorescence intensities for that sample prior to analysis to control for individual differences in seroreactivity to the IVTT reaction mixture.SDBS is the signal from a DBS sample, Sserum is the signal from the matched serum sample, Smax is the maximum signal, and r is the “recovery,” or the factor by which the antibody concentration in the DBS eluate is reduced relative to the serum concentration. Because the dilution of DBS eluates approximates that of a 1:100 serum dilution, the theoretical maximum recovery is 100%.Recovery of IgG from DBS relative to matched serum samples was estimated by least squares fitting (GraphPad Prism) to a model derived from the ligand-binding equation :1\documeBackground-subtracted fluorescence intensities were log2 transformed for group comparisons and regression analysis. A serorecognized antigen was defined as an antigen for which the average log2 transformed background-subtracted fluorescence intensity was significantly greater than that of the malaria-naïve North American control group . Population seroreactivity was defined as the average seroreactivity of the population for antigens that were serorecognized.P. falciparum usPCR-positive infections, responses from P. falciparum usPCR-positive individuals were compared to usPCR-negative (including P. vivax-positive) individuals using a regularized logistic regression [To identify IgG markers for gression  performegression  on the cAll supporting data collected in this study are provided in Additional files P. falciparum and P. vivax prevalences of 8.7% and 5.6 %, respectively, by usPCR in 2015 [The median age of participants was 35 years (range: 2–84), and 66% were female. Male participants were younger (median 17.5 years) than female participants (median 37.5 years). Despite the previous finding of  in 2015 , no part in 2015 .P. falciparum genome. Figure Matched DBS and serum samples were probed on protein microarrays populated with antigen fragments from the reference 3D7 Despite the loss of IgG activity with DBS, good agreement was seen in antigen and population trends between the two sample matrices. As expected, fewer fragments were serorecognized by the endemic groups in DBS eluates (156) compared to serum 231). However, 151 fragments were serorecognized from both DBS and serum, indicating high overlap between the two sample types. Moreover, the average seroreactivity against serorecognized fragments was strongly correlated between the two sample matrices  . The log2-transformed fluorescent signal from all individuals against the differential antigens are shown in Fig. Using the same elution methodology for the matched DBS and serum study, antibodies were extracted from DBS and IgG activity was probed on a protein microarray populated with P. falciparum. Notably, the most influential antibody response was that against P. falciparum circumsporozoite protein (CSP), which had a strong negative impact on the odds of P. falciparum-positivity. Figure P. falciparum-positivity, broken down by age and gender. While there was no noticeable difference in model performance for males and females, age had a significant impact on how well the model performed. IgG responses were better predictors for younger individuals and were not predictive of P. falciparum-positivity in older adults (> 41). Across all individuals included in the study, model area under the curve (AUC) of the ROC was 0.772 and performance characteristics were 58% sensitivity, 85% specificity, 88% negative predictive value, and 52% positive predictive value, relative to usPCR.A regularized logistic regression model was then fit using leave-one-out cross-validation to identify which IgG responses may be useful for classifying cases and controls. Table P. falciparum malaria.This study demonstrated that DBS are viable samples for probing IgG responses on malaria protein microarrays. Despite a loss of signal relative to serum, IgG activity from DBS was successfully quantified, and similar trends were seen for antibodies derived from DBS and serum. Antibodies eluted from DBS were also found to be useful for identifying informative IgG responses in individuals who have asymptomatic, subpatent Matched DBS and serum samples were probed on Pf250 protein microarrays, and approximately 30% of the IgG activity in serum was recovered from DBS. This recovery was lower than expected, as ELISA-based methods have reported up to 70% recovery of malaria IgG [Although recovery of IgG activity from DBS was lower than expected, similar antigen and population trends were observed for antibodies obtained from both sample matrices. There was a large overlap of serorecognized antigens, with over 65% of the fragments that were recognized in serum also being serorecognized in DBS eluates. Average antibody response signal against serorecognized fragments was strongly correlated between the two sample matrices, indicating that DBS eluates provided reliable quantitative results compared to serum. Similarly, despite the overall lower signal from DBS, population trends in seroreactivity by gender and by age were comparable between the two sample matrices. Thus, IgG activity measured on protein microarrays from DBS can be relied on for observing antigen and population trends in malaria-endemic areas. These results likely extend to infections beyond malaria for which serosurveillance is routinely used to track exposure or vaccination coverage, and DBS collection would be more logistically feasible and cost effective than serum collection for serosurveillance of a number of infectious pathogens.P. falciparum infections. Previously collected and banked DBS were eluted using the same method as the serum/DBS comparison study and probed on Pf250 microarrays. While the study was designed to identify markers of asymptomatic infection, it is important to note that serological profiles also reflect past malaria exposure, which is likely associated with infection status. Among the 18 antibody responses that affected the odds of usPCR positivity, 15 were positively correlated and three were negatively correlated with P. falciparum infection. The antibody response with the greatest magnitude of negative or positive association with asymptomatic infection was to CSP, a leading malaria vaccine candidate [P. falciparum-positivity, consistent with CSP antibodies having a protective effect against infection as previous studies have reported [P. falciparum exposure or asymptomatic infection using similar protein microarray methods with serum samples [P. falciparum infection or of infection incidence in the last year [P. falciparum-specific immune responses on protein microarrays.The case-control study aimed to identify serological signatures of asymptomatic andidate . In thisreported , 35. Man samples , 37. Forast year . These cThe antibody responses against the 18 antigens in Table The test characteristics of the model relative to usPCR were modest across all samples, with 58% sensitivity, 85% specificity, 88% NPV, and 52% PPV, suggesting that these serological signatures alone would not be sufficient for accurately identifying usPCR-positive individuals. However, it is important to note that all of the individuals included in this case-control study were RDT-negative. While the model does not accurately capture all usPCR-positive infections, it does capture more of the asymptomatic reservoir than standard RDTs currently used for malaria diagnosis, though at the cost of reduced specificity, particularly for adults or individuals with a history of previous exposure. Given this improved sensitivity over RDTs, serological markers could be useful intermediate tools for identifying exposure to ultra-low density malaria infections, particularly if serosurveillance strategies target individuals with less previous exposure, such as children, as sentinels for recent population exposure.P. falciparum cases and controls were probed to identify a panel of antibody responses associated with increased odds of asymptomatic malaria infection. The use of DBS on protein microarrays enables high-dimensional serological studies in populations where serum collection, transport, and storage would be otherwise impossible.Screening malaria-specific antibody responses on protein microarrays can help identify immune factors that elicit protection from malaria infection, disease, and transmission, as well as for markers of past exposure. Most malaria protein microarray work has relied on serum as a sample matrix, which requires immediate laboratory processing and continuous cold chain. This study demonstrated that malaria-specific immune responses can be detected, quantified, and analysed from DBS on protein microarrays. As a proof-of-concept, DBS from asymptomatic Additional file 1. Sample metadata and Pf250 signal for matched DBS and serum study.Additional file 2. Sample metadata and Pf250 signal for case-control study.


Azithromycin is a broad-spectrum antibiotic that has moderate antimalarial activity and has been shown to reduce all-cause mortality when biannually administered to children under five in high mortality settings in sub-Saharan Africa. One potential mechanism for this observed reduction in mortality is via a reduction in malaria transmission.Plasmodium falciparum and measured tympanic temperature for all children. Caregiver-reported adverse events and clinic visits were recorded at the day 14 visit.We evaluated whether a single oral dose of azithromycin reduces malaria positivity by rapid diagnostic test (RDT). We conducted an individually randomized placebo-controlled trial in Burkina Faso during the high malaria transmission season in August 2020. Children aged 8 days to 59 months old were randomized to a single oral dose of azithromycin (20 mg/kg) or matching placebo. At baseline and 14 days following treatment, we administered a rapid diagnostic test (RDT) to detect P = 0.65). Fifteen percent of children in the azithromycin arm had a fever ≥ 37.5 °C compared to 21% in the placebo arm (P = 0.12). Caregivers of children in the azithromycin group had lower odds of reporting fever as an adverse event compared to children in the placebo group . Caregiver-reported clinic visits were uncommon, and there were no observed differences between arms (P = 0.32).We enrolled 449 children with 221 randomized to azithromycin and 228 to placebo. The median age was 32 months and 48% were female. A total of 8% of children had a positive RDT for malaria at baseline and 11% had a fever (tympanic temperature ≥ 37.5 °C). In the azithromycin arm, 8% of children had a positive RDT for malaria at 14 days compared to 7% in the placebo arm (We did not find evidence that a single oral dose of azithromycin reduced malaria positivity during the high transmission season. Caregiver-reported fever occurred less often in children receiving azithromycin compared to placebo, indicating that azithromycin may have some effect on non-malarial infections.Trial registration Clinicaltrials.gov NCT04315272, registered 19/03/2020 Plasmodium falciparum parasite . Th. Th11]. Anopheles gambiae complex, and the Anopheles coluzzi species is most commonly found in Nouna [P. falciparum is the primary malaria species infecting humans in the region [Children were enrolled in mid-August 2020 at the Nouna District Hospital. The primary endpoint occurred 2 weeks following enrollment in September 2020. In this setting malaria transmission is highly seasonal and typically peaks from July through October during the rainy season . Seasonain Nouna . P. falce region .Mobilizers sensitized the community by visiting households with children under 5 based on the most recent census conducted by the Nouna Health and Demographic Surveillance Site (HDSS) . Study sAt baseline, study staff conducted a survey with the caregiver. Questions included breastfeeding status, maternal age, the mother’s level of education, literacy, and gravidity. The study staff member utilized a custom mobile application to input all data into a handheld tablet .OnSite Pf/Pan antigen rapid test  was used to detect Plasmodium falciparum among all participants regardless of presence of fever at baseline and 14 days following treatment. Study staff measured tympanic temperature for all children at both study visits using the Braun Thermoscan 7 Digital Ear thermometer . Fever was defined as tympanic temperature ≥ 37.5 °C. Febrile children and those with a positive malaria RDT were referred for care.An Enrolled participants were randomized to receive a single oral dose of azithromycin (20 mg/kg) or equivalent volume of matching placebo. The placebo was identical to the azithromycin in appearance and taste. Dosage was determined by height stick approximation if the child was able to stand or by weight if the child was under 12 months of age and/or unable to stand . The medThe randomization sequence was generated by the study statistician without blocking or stratifying in R. Unique participant identification numbers were created which were associated with the randomization assignment and uploaded into the electronic data capture platform. The trial was double masked and all field team members and participants were masked. The allocation concealment mechanism was a combination of the unique participant IDs and matching drug labels. The drug was labeled with 1 of 8 different letters to avoid the possibility of unmasking. After a participant ID was assigned to the child, the field team member scanned the ID into the electronic mobile application which then informed the team member which letter to treat the child with.Caregivers presented to the hospital 14 days after the baseline visit. A brief interview was conducted with the caregiver regarding any adverse events experienced by the child since treatment including abdominal pain, diarrhea, vomiting, constipation, or skin rash. These adverse events were specifically asked based on findings from previous pediatric azithromycin trials –21. CareThe primary outcome for this trial was Shannon’s and Simpson’s diversity index of the gut microbiome at 6 months and will be reported separately. Secondary outcomes included malaria status at 14 days post enrollment determined by RDT, clinical malaria at 14 days post enrollment defined by a positive RDT and tympanic temperature ≥ 37.5 °C, caregiver-reported adverse events, and clinic visits.The sample size was based on the primary outcome of the trial which was Shannon’s and Simpson’s diversity index of the gut microbiome. For the malaria outcome, we assumed 80% power to detect a significant effect with a sample size of 225 per arm, no loss to follow-up, and RDT positivity prevalence in the control group of 10%. Given these assumptions, the trial was powered to detect an absolute difference of 6.6%.Descriptive baseline characteristics were summarized with proportions for categorical variables and medians and interquartile ranges (IQR) for continuous variables. The proportion of participants with a fever (defined as tympanic temperature ≥ 37.5 °C) at the time of the follow-up visit was calculated. We also calculated the proportion of children with a positive malaria RDT at the 14-day visit. Caregiver-reported health center visits were classified by arm and reason for the visit. Lastly, we calculated the proportion of children experiencing any adverse event as reported by their caregiver by study arm as well as each individual adverse event. Odds ratios (OR) and 95% confidence intervals (CI) were computed for each outcome using an unadjusted logistic regression model with the randomized treatment arm assigned as the predictor. Because RDTs can remain positive for several weeks even if there is no longer an active infection, we restricted the 14-day RDT model to children who were RDT negative at baseline as a sensitivity analysis. All analyses were intention-to-treat, where all randomized children were included regardless if they received their randomized assignment or not. Analyses were performed in Stata version 15.1 .A total of 449 children were enrolled in the trial with 221 in the azithromycin arm and 228 in the placebo arm . At the 14-day follow-up, 33 children (15%) in the azithromycin group had a tympanic temperature ≥ 37.5 °C versus 47 children (21%) in the placebo group. Three percent of children in both arms had a positive malaria RDT plus fever at 14 days. There were 15 participants with a negative RDT at baseline which then became positive at 14-days . We did not find evidence of an effect of azithromycin on RDT positivity without fever . Diarrhea was the most common reason for a health center visit across both arms .Caregivers of 3% of participants reported their child had a health center visit by the 14-day visit with no evidence of a difference between arms .The results of the sensitivity analysis did not qualitatively change the results as we found no evidence of an effect of azithromycin on 14-day malaria RDT positivity in children with a negative RDT at baseline . Diarrhea was the most commonly reported adverse event and there was no significant difference between study arms . We did not find evidence of a difference in any other adverse events.Overall, 12% of caregivers reported that their child experienced at least a single adverse event in the 14-day period after treatment with 20 in the azithromycin arm (9%) and 32 in the placebo arm (14%)  that was administered at the same time as the trial within the Nouna community. SMC distributions with sulfadoxine–pyrimethamine (SP) and amodiaquine (AQ) to children aged 3–59 months occurred monthly from July 13stration . Concomistration –26.Community-level distribution of AZ could be more effective for malaria control compared to individual-level distribution as several community based trials have demonstrated that mass AZ distribution reduces malaria parasitemia , 27, 28.We observed a lower probability of caregiver-reported fever in the azithromycin group compared to the placebo group, suggesting that azithromycin may have an effect on non-malaria fevers. Gastroenteritis and pneumonia were reduced 30% and 34% respectively in a West African azithromycin trial, suggesting AZ may lower other fever-inducing infections commonly found in sub Saharan Africa , 25. TheThe implications of utilizing an antibiotic, such as azithromycin, for malaria prophylaxis should be considered. Selection pressure for antimicrobial resistance can arise following over-administering antibiotics. Resistance to antibiotics could render treatment against other bacterial infections ineffective, which is a serious concern for global health . The resLimitations for this study include the sole use of an RDT rather than PCR or microscopy for defining malaria positivity. Some trials have documented low RDT sensitivity in this setting with results that may vary by parasite density , 35. RDTAzithromycin did not lower malaria positivity as measured by RDT within a 14-day period when administered as a single dose to children 1–59 months old. The point prevalence of fever was similar between the azithromycin and placebo groups, but caregiver-reported fever over the 14-day period from treatment occurred less often among children receiving azithromycin compared to placebo. We found no evidence that individual-level treatment with azithromycin affected malaria prevalence 2 weeks after treatment.


P. falciparum increased from 11.4 to 19.1% in Megiar and 12.3 to 28.3% in Mirap between 2014 and 2016, with focal hotspots observed in these villages in 2014 and expanding in 2016. Prevalence of P. vivax was similar in both years  and spatial risk heterogeneity was less apparent compared to P. falciparum. Within-village hotspots varied by Plasmodium species across time and between villages. In Megiar, the adjusted odds ratio (AOR) of infection could be partially explained by household factors that increase risk of vector exposure, such as collecting outdoor surface water as a main source of water. In Mirap, increased AOR overlapped with proximity to densely vegetated areas of the village. The identification of household and environmental factors associated with increased spatial risk may serve as useful indicators of transmission hotspots and inform the development of tailored approaches for malaria control.Malaria risk is highly heterogeneous. Understanding village and household-level spatial heterogeneity of malaria risk can support a transition to spatially targeted interventions for malaria elimination. This analysis uses data from cross-sectional prevalence surveys conducted in 2014 and 2016 in two villages (Megiar and Mirap) in Papua New Guinea. Generalised additive modelling was used to characterise spatial heterogeneity of malaria risk and investigate the contribution of individual, household and environmental-level risk factors. Following a period of declining malaria prevalence, the prevalence of  The main interventions are vector control with long-lasting insecticide treated bed nets (LLINs), indoor residual spraying (IRS), rapid diagnostic tests (RDTs) for prompt and improved case diagnosis, and treatment with artemisinin combination therapy (ACT)2. Although uniform application of these standard control methods has been effective in reducing the burden of malaria, global progress has stalled and some countries are reporting an increase in malaria incidence1.Increased investment towards the scale-up of malaria control interventions led to a global decline in malaria incidence between 2010 and 2018, from 72 to 57 cases per 1000 population at risk4. The individual risk of a Plasmodium spp. infection and heterogeneity in that risk is influenced by climate, physical geography, land use, human behaviour and social factors at village or household level, and variations in health service delivery. As malaria transmission decreases, infections tend to become clustered in localised communities, households, or groups of people. In a geospatial sense, these clusters, known as “hotspots”, are defined as areas where there is a higher than expected risk of malaria Plasmodium spp. infections compared to surrounding areas, reflecting a higher than average level of malaria transmission intensity. Hotspots have been reported in several studies at various spatial scales from province or district levels right down to village and household levels9.As endemic countries make progress towards the goal of malaria elimination, malaria transmission has been observed to become more heterogenous2. However, the spatial scale chosen should also be determined by local epidemiology, data availability and programmatic objectives. As countries move towards elimination, hotspots at the village-level spatial scale can serve as a reservoir of the Plasmodium parasite in a receptive environment, thereby sustaining and fuelling ongoing transmission or resurgences of malaria10 and threatening achievements made in malaria elimination settings. Fine-scale spatial targeting of malaria interventions to high-risk households or villages may therefore be a favourable approach to inform operational decisions for malaria control and elimination particularly in the context of maximising limited resources13. Moreover, a recent review has highlighted that the limited effectiveness of spatially-targeted interventions observed in several studies could be improved with better understanding of underlying drivers of ongoing transmission, better data collection and measurement of malaria hotspots14.WHO recommends stratification at spatial scales that are commensurate with transmission levels so that appropriate targeted interventions can be achieved15, encouraging the realisation of its national vision to eliminate malaria by 203016. The success of the program has been attributed to national distribution of LLINs17, scale-up of compulsory testing of suspected malaria cases with RDTs, and the switch to ACT for treatment18. Despite a standardised approach in the implementation of these measures, the reduction in malaria prevalence has not been uniform in previous high-burden areas across the country and considerable heterogeneity in malaria burden both across and within provinces has been documented15. The national malaria indicator survey (MIS) conducted in 2016/2017 estimated an increase in national malaria prevalence to 7.1%, with 5 out of the 18 surveyed provinces recording 8–16% prevalence and the remaining provinces 0–5%. Within lowland provinces, pockets of villages with higher prevalence were also reported15.In Papua New Guinea (PNG), the scale-up of malaria interventions has resulted in a significant overall reduction in nationwide malaria prevalence from 11% in 2009 to less than 1% in 2014The standardised application of additional control interventions  using entire provinces as the implementation unit may not be cost effective if malaria risk at the district, village and household levels exhibits large degrees of heterogeneity. This may be expected given the great diversity in human behaviours and physical environments in PNG. Understanding malaria risk heterogeneity at the village level could therefore help identify geo-spatial, environmental, household, and behavioural risk factors that are perpetuating malaria transmission so that sub-Provincial micro-stratification plans can be developed, and control tools and approaches optimized. Specifically targeting appropriately identified foci of transmission with a suite of additional control tools at high coverage could accelerate transmission reduction as compared to continued uniform application of existing control interventions nationwide.This study aims to characterise and quantify the fine-scale spatial heterogeneity of malaria infection and its changes over time in two villages in PNG, drawing upon data from two cross-sectional studies—one conducted in 2014 when national prevalence was very low, and one conducted in 2016/17 when prevalence had increased. Using a geospatial statistical modelling approach, we aimed to identify if within-village hotspots existed in 2014 and how they may have changed over this period of time as prevalence increased. In addition, we sought to identify specific risk factors that may have been associated with these hotspots.19 and 2016–2017 (shortened as 2016 from hereon)21. These surveys covered a number of villages on the north coast but for the purpose of this study, two villages that were included in both surveys, Megiar and Mirap, were selected to compare hotspots and risk factors between 2014 and 2016. A hotspot is defined in this study as an area with a higher than expected malaria burden were the disease to be homogeneously distributed across the study area. Geospatial analysis was an explicit aim of the 2016 survey but not of the 2014 survey. The 2014 survey utilised a convenience sampling approach, which can potentially bias participant selection. Despite this, the geographical distribution of sampled households was representative as shown in Fig. Independent cross-sectional malariological surveys were conducted in PNG, Madang Province in 20142 for Megiar and 2 km2 for Mirap. The households sampled in 2014 and 2016 were not the same, although 32% of households in Megiar and 21% in Mirap were common to both surveys , Access Bio, USA) was performed and those positive by RDT were treated according to PNG Standard Treatment GuidelinesGeo-location of households was determined by GPS recording devices with a resolution of approximately 3–10 m in 2014 and 2016. The primary unit of analysis was the individual. In addition to the individual-level data collected from all participants, information on household characteristics such as type of construction materials used, toilet facilities, source of drinking water, income source of head of household and household agricultural assets was also collected in 2016 through questionnaires administered to the head of the household. Household-level variables were assigned to each individual residing within the household that took part in the survey.23.As part of each survey, 250–300 µl of capillary blood from a finger prick sample was collected for detection of malaria parasites by light microscopy as well as by qPCR. Thick/thin blood smears were prepared on slides and examined independently by two microscopists (WHO-certified Level 1–3), with discrepancies resolved by a third microscopist (WHO-certified Level 1 Expert). Parasite densities were calculated from the number of parasites per 200 or 500 white blood cells (WBC) (depending on parasitaemia) and an assumed total peripheral WBC count of 8000 per µl, with the final density recorded as the geometric mean of the two valuesPlasmodium parasite species, DNA was extracted from 200 µl of whole blood followed by qPCR. Details of laboratory procedures were previously described for the 2014 samples19 and a sub-set of the 2016 samples21. A sub-set of the 2016 samples was extracted using NucleoMag ® Blood Beads , eluted in 200µL of MBL 5 buffer and stored in 96 well plates at − 30 °C until their use. Two duplex TaqMan qPCR assays were performed combining specific primers and probes targeting the 18 s rRNA gene region for P. falciparum and P. vivax in one reaction, and P. malariae and P. ovale in another, as reported by Rosanas-Urgell et al.24, with slight modifications.For molecular detection of 25, which itself has previously been reported to have a positive relationship with malaria infection risk26. It is therefore suitable for our models given the presence of dense vegetation surrounding households in the surveyed villages. NDVI is calculated using the standard equation:http://earthexplorer.usgs.gov) and used as there was minimal cloud cover over our study areas on that day and we assumed that vegetation did not vary significantly over the two timepoints. The vegetation density is similar in both villages with a median NDVI value of 0.5  was used to create a socio-economic status (SES) index from 6 factors derived from the 2016 survey data: (1) highest level of school completed by head of household, (2) main source of income of household, (3) number of chickens owned in household, (4) number of pigs owned in household, (5) number of dogs owned in household, and (6) number of cats owned in household. No autocorrelation between these factors was observed and internal validation of the SES index was determined by assessing correlation with household characteristics using the Spearman’s rank-order correlation test.https://www.R-project.org/). Data from 2014 and 2016 were treated as independent data sets. Individual and household characteristics were compared between years using Chi-squared and Mann–Whitney tests. P. falciparum and P. vivax prevalence (by light microscopy and qPCR) was estimated by year, age group and village and compared between years and age groups using Chi-squared tests.Data analysis was performed with R v.3.6.2 software  was summarised by year and village. Comparisons of parasite density between the two time points for each species in each village was performed by Wilcoxon rank test.Generalised additive modelling (GAM) was used to define hotspots of malaria risk. Spatial GAM outputs are continuous surfaces of variable shape to quantify the spatially attributable risk or probability of infection across the whole study area. GAM takes a semi-parametric approach that allows for construction of an adjusted odds ratio (AOR) surface that includes the effects of covariates, and a spatially smoothed function of the residual spatial risk. Compared to a generalised linear model, which assumes all covariates have a linear relationship with the outcome, the GAM has flexibility to model complex non-linear relationships.27 in R. The outcome of infection status for P. falciparum and P. vivax was modelled separately as a binomial response through a logit link function. Covariates chosen for the model were risk factors such as age and sex that have been epidemiologically associated with malaria infection and also other risk factors that may impact exposure to vector biting. These covariates were available in our data and were chosen based on existing evidence of their causal relationship (both direct and indirect) with malaria infection as described by a directed acyclic graph. As such we have not provided any adjustment for multiple testing and our model was an adjusted multivariate model. A base model comprising of vegetation density (NDVI) and individual-level risk factors—age, sex and LLIN use was created to estimate changes in AOR between 2014 and 2016. LLIN use was regarded as an individual behavioural risk factor modelled as a binary variable, Yes–No, in response to the prevalence survey question “did you use a bednet last night?”. A second extended model was also created using the base model covariates as well as household-level risk factors collected in the 2016 survey as covariates. This was to determine if some of the residual spatial risk predicted in the base model could be explained by household risk factors. Household level risk factors include socioeconomic status29, household construction materials for the wall and the roof30 and the type or lack of window screening31, type of toilet facility and source of drinking water  were included a priori as potential malaria risk factors.The GAM framework was implemented through the ‘mgcv’ packageP represents the probability of infection at location i, a represents the intercept, b represents the parametric coefficients for n categorical variables (x), c represents the parametric coefficient for SES (continuous variable), and u and v represents the smoothing function of a thin plate regression spline on age and vegetation density, thus accounting for the non-linear relationship between these two predictors and malaria infection. The ‘mgcv’ GAM model allows us to simultaneously estimate from the data all possible values for the smoothing parameters and obtain the optimal smoothing parameter by maximizing the penalized likelihood function. For this purpose, we have set the smoothing parameter estimation method attribute in the model to the restricted maximum likelihood (REML) method. Preliminary modelling showed that SES had a linear relationship and therefore was modelled using a simple parametric term. The spatial effect of household location L (longitude and latitude coordinates) was modelled as an interactive term through the thin plate regression spline function, w, with basis function following a Gaussian process. The mathematical formulation for the base model is similar to the extended model but with the removal of the c(SESi) term and a reduced matrix of n categorical variables to individual level factors of sex and LLIN use. We used empirical variograms to investigate the model residuals to ensure that there was no further household spatial dependency and autocorrelation in our models.The GAM model used in our analysis was structured as follows:The GAM was then used to predict the adjusted log odds for malaria infection over a continuous space across the study area. To accomplish this, a prediction grid using latitude and longitude with a resolution of 0.0001 degrees was created, encompassing the study area. Each grid intersection point therefore formed a location for model prediction. To complete the covariates for prediction, we created an ‘average’ model by taking the mode and median values for categorical and continuous covariates respectively so that the variation of the predicted log odds was due to its spatial location in the study area. The NDVI covariate values were projected on the prediction grid to capture the actual variation of vegetation across the study area. A ‘null’ model was also created by omitting all covariates to provide a reference for average odds of infection over the entire study area . This reference was then used to calculate the AOR of spatial effects at each location. A hotspot, as predicted from the GAM model, is therefore defined as an area with AOR greater than 1, representing locations where malaria risk was higher than what would be expected were the disease to be homogeneously distributed across the study area. Covariate effects were expressed as AORs.Study protocols for both surveys were approved by the Institutional Review Board of the PNG Institute of Medical Research (IRB 1116 & 1517), the PNG National Medical Research Advisory Committee (MRAC 11.21 & 16.08), Alfred Precinct (Project No. 721/18) and Monash University (Project No. 18151). Written informed consent was obtained from all study participants or their parents or legal guardians and research was conducted in accordance with the Declaration of Helsinki.In Megiar, 509 individuals living in 121 households were included in the 2014 survey and 601 individuals in 132 households were included in the 2016 survey. In Mirap, 529 individuals living in 120 households and 672 individuals living in 127 households were included in 2014 and 2016 respectively.There were no statistically significant differences between sex and age distributions of study participants in both years. LLIN usage in both years in both villages was > 80% . By contrast, the prevalence of P. vivax infection was similar over the two years . P. vivax was dominant in 2014 with a higher prevalence than P. falciparum. However, in 2016, P. falciparum was the dominant species, particularly in Mirap. The prevalence of malaria infection as detected by light microscopy (LM) and qPCR for each village at each of the two time points is summarised in Table The prevalence of qPCR-detected P. falciparum and P. vivax by qPCR in both villages was observed to increase with age. P. falciparum prevalence reached its peak in the 11–15 years age group in 2014 and in the 16–20 years age group in 2016  in 2014 and 84.6 copies/µl  in 2016, while for P. falciparum, parasite density was 52.6 copies/µl  in 2014 and 431.7 copies/µl . In Mirap, geometric mean for P. vivax was 29.7 copies/µl  in 2014 and 71.6 copies/µl  in 2016, while for P. falciparum, parasite density was 117.3 copies/µl  in 2014 and 183.8 copies/µl  in 2016. These differences between years were statistically significant except for P. falciparum in Mirap  , except for P. falciparum in Mirap in 2014 (p = 0.09), as shown in our models. The effect of age on probability of infection is shown as smoothed partial effect plots in Supplementary Fig. P. vivax , whereas sex was not a significant risk factor in Mirap  but was not associated with risk of P. falciparum infection.In Megiar in 2016, males had a significantly higher odds of P. vivax infection  . In contrast, traditional materials such as bamboo or sago leaf stalks that were used to construct the walls of houses were associated with increased odds of infection compared to modern materials such as cement, bricks, or iron sheets (AOR range = 1.6–5.7), but these estimates were not statistically significant and the wide confidence interval is indicative of sparse data available   was generally observed to have a weak positive non-significant relationship with malaria infection in both villages  in both years, although more evident in 2016  infections was observed, indicative of higher transmission. P. falciparum and P. vivax hotspots were observed in these village and their location, size and intensity differed according to village-specific characteristics associated with transmission. Hotspots for P. falciparum were more clearly observed than for P. vivax.Following a period of rapidly declining P. falciparum was observed in Megiar in both years, even though prevalence of infection and parasite density increased between 2014 and 2016. The hotspots increased in size between 2014 and 2016 and an upward shift in the age-specific peak prevalence to the 16–20 years age-group was also observed. Spatial risk heterogeneity was observed for P. vivax in Megiar, but risk was more focal. Although P. vivax prevalence was similar in both years, the density of infections increased significantly in 2016 and an upward shift in the peak prevalence to the 11–15 years age-group was observed. Much of the spatial risk for both species in Megiar could be explained by household risk factors. In particular, the use of surface water as a drinking water source and use of corrugated iron roofing, both of which are more likely to increase the risk of vector exposure.Spatial risk heterogeneity for P. falciparum and P. vivax was homogeneous in the area of Mirap that was sampled in both years. It is possible that in this highly populated village, transmission had not yet declined to a level in 2014 where hotspots could be observed. P. falciparum prevalence increased significantly in 2016 and peak prevalence shifted to the 16–20 years age group, but the mean density of infections was similar. P. vivax prevalence was similar in both years, but parasite density increased significantly in 2016. Household factors did not explain the residual spatial risk, instead a hotspot was predicted for the sparsely populated south-west area with dense vegetation, which showed a significant positive association with infection risk.In contrast, spatial risk for 33. It is possible that the 2014 hotspots acted as a reservoir of infections at a time when LLINs with reduced bioefficacy34 were distributed in the area in 201535, thereby fuelling the expanded hotspot in 2016. Entomological data from the area also showed that infective biting rates were observed to increase by threefold in Megiar and 18-fold in Mirap between 2010 and 2016 and that the majority of vectors were caught outdoors . Differences in vector competence between P. falciparum and P. vivax in PNG has been reported36 and may also be a factor underlying hotspot variation observed in our study.In Megiar, there was evidence that 2014 hotspots may have expanded by 2016, supporting observations from other settings that hotspots fuel ongoing transmission if neglected37 and this may have increased the risk for people living in or frequenting this area. Similarly, the observed ‘neutral spot’ that has a lower AOR for P. falciparum infection, is a cleared and more populated area of the village, consisting largely of the main road, community buildings and considerably less vegetation and forest. The contrast between model-predicted low (uniform) AOR in an area where the major proportion of P. falciparum infections and households are found, to model-predicted high AOR in an area where a small proportion of the village-specific P. falciparum prevalence is located, suggests that malaria transmission could be predominantly occurring in these vegetated non-habited areas where village residents frequently walk through20, increasing the opportunities for vector exposure.The hotspot observed in Mirap in 2016 warrants careful interpretation, notably because the density of houses in this area is low, which may have biased the model risk estimates. We do however note that this hotspot coincides with a densely vegetated area of the village and such environments could be conducive for vector breeding and activityP. vivax prevalence is quite consistent with other co-endemic settings where in the face of intensive malaria control to reduce transmission and disease burden, P. falciparum prevalence decreased but P. vivax prevalence remained relatively stable or even increased due to relapses38. The homogenous nature of the observed spatial risk for P. vivax is likely due to the unique biology of P. vivax, whereby infections are due to a combination of newly transmitted infections and relapsing infections from dormant liver stage hypnozoites. In PNG, relapsing infections can occur frequently and account for up to 80% of P. vivax infections39. Frequent occurrences of P. vivax relapses, which are not dependent on vector exposure, may therefore have overshadowed and either focalised or homogenised the detection of any P. vivax ‘transmission hotspots’ in our models. New mosquito-derived P. vivax infections are obviously dependent on vector exposure, but importantly human to mosquito transmission may stem from either newly infected or relapsed individuals. It is therefore important to consider if ‘infection’ hotspots are also areas where there may be intense vector activity and/or greater opportunities for human-vector interaction.The observed pattern for P. falciparum peaking in 15 to 20 years old adolescents and P. vivax in 10 years old children, which translated to highest parasite prevalence in those ages as well. This is consistent with other studies where peak prevalence and odds ratios of P. vivax were observed in younger children (6–12 years of age) than those for P. falciparum (12–20 years of age)40. Behavioural data observed from this village, confirmed that school-aged children walked to school and the further they lived away from school, the higher their potential for vector exposure as they tended to wake up earlier before dawn20. Our data suggests males are at higher risk, which may be explained by the lack of protective clothing for boys and men who tend to move about in shorts, short-sleeved shirts or even shirtless from before dawn to well after dusk20. Men have also been reported to use LLINs less often than women41.At the individual level, age remained a significant risk factor with probability of infection for 44. LLINs have also been shown to have no further preventive effect in malaria reduction following a rebound in malaria prevalence after a long period of decline45. This could suggest that vector biting was occurring at earlier times when individuals were not sleeping and therefore not under LLINs or biting outdoors as previously documented in PNG47 and other settings50. Additionally, the reduced bio-efficacy of LLINs distributed in PNG since 201334 is likely to be a major contributing factor towards the lack of protective effect of LLIN when the third round of LLIN distribution occurred in this area in 201535. This coincides with the resurgence observed in the surveyed villages in 2016.Although an increase in prevalence was observed between 2014 and 2016, self-reported LLIN usage remained high at 82% in Megiar and increased from 85.6 to 93.9% in Mirap. This is consistent with studies showing that the effectiveness of high-coverage LLIN usage plateaued in further reducing human-vector contact and malaria prevalence51. In our study, households needing to access surface water serve as a proxy risk factor for vector exposure in this setting. The likely need to venture into dense areas of garden/forest to access the nearby river or stream for water collection places the individual at higher risk of mosquito exposure. While it may be argued that water collection and other such activities would tend to occur at dawn, dusk, or daytime rather than at night when peak vector biting rates are expected, recent studies in PNG and elsewhere have reported a shift in vector biting behaviour to feeding outdoors in the earlier hours of the evening, at a time when individuals were still outdoors and not protected by LLINs, as well as at early dawn52. This is supported by behavioural studies conducted in this region of PNG, highlighting water-related household chores taking place in the early morning and evening, often performed by school-aged children and likely increasing vector exposure20. In Mirap, only a small percentage of households (8%) used surface water as their drinking water source with most households (79%) having access to nearby wells. Use of wells was not a significant risk factor in our models, possibly related to them often being located within a village in close proximity to houses. No households indicated use of wells in Megiar, highlighting a distinct difference in this behaviour between the two villages.Incorporating household characteristics into the model explained residual spatial risk observed in Megiar but not in Mirap. The importance of household-level over individual-level factors in predicting malaria risk has been shown in other settings such as Cambodia31 and in some settings, specific household modifications have demonstrated efficacy as additional tools alongside LLINs and IRS53. In this study, roofs made from thatched grass or sago palm leaves were associated with up to two-fold reduced odds of malaria infection compared to corrugated iron roofs, suggesting that in this context traditional materials or the style of construction used with traditional materials may reduce vector entry. It may be that houses with corrugated iron roofs were built with openings or with open eaves in order to improve ventilation and help cool the houses30, but in the process has increased opportunity for vector entry as shown in settings such as in Kenya and Tanzania54. Houses with corrugated iron roofs can also be hot at night which may lead to people tending not to use LLINs when they sleep55. Further investigation and finer classification of roof construction as closed/intact and -open/with open eaves will be useful to further elucidate the relationship between roof as a proxy risk factor of vector exposure and malaria infection. Additional tools such as eave ribbons (containing passive mosquito repellent such as transfluthrin)56 and eave tubes (containing insecticide-treated discs)57 may also warrant further investigation for effectiveness in the PNG setting.House design is also known to be an important determinant of malaria riskOur study has several limitations. Firstly, the two surveys are independent with less than 32% of participants involved in both surveys and the sampling strategy was also different. Sparse sampling in certain areas of the village may also have resulted in biased overestimated prediction of malaria risk as observed in Mirap in 2016. The 2014 survey did not collect detailed data on household characteristics, preventing investigation of household risk factors that may have been sustained throughout the two timepoints. Self-reported LLIN use may be overestimated due to recall and courtesy bias. Additional studies could extend this analytic framework to include other data such as entomological activity, and frequency of residents’ movement within village such as to rivers and vegetated areas. Furthermore, cohort studies with molecular force of infection data and/or spatially explicit health facility surveillance conducted over several years may provide additional evidence to advance our understanding of village-level spatio-temporal dynamics of transmission.This study used a GAM approach at the village level to identify hotspots with higher spatial risk after adjusting for a range of known risk factors. Different spatial, environmental, and household risk factors were identified in two villages despite their close proximity to each other. Collecting surface water for drinking water was a household risk factor in Megiar and being surrounded by dense vegetation was a risk factor in Mirap. In both cases, these risk factors are proxies for vector exposure outdoors as villagers move about in their surroundings, suggesting a role for the application of tailored approaches targeting outdoor transmission. These results provide a rationale for consideration of the utility of sub-Provincial spatial risk mapping to identify key drivers of ongoing transmission and guide the application of additional malaria control interventions to further accelerate transmission reduction. To improve the effectiveness of interventions aiming to interrupt persistent ongoing transmission, new approaches, tools, and indicators that can better predict spatial risk and identify stubborn hotspots are required.Supplementary Information.