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opencc-by-4.0Dec 2022View details →

Fig. 7. MSP-1 in Plasmodium relictum MSP-1 capture antigen-based ELISA for detection of avian malaria antibodies in African penguins (Spheniscus demersus)

Fig. 7. MSP-1 capture antigen-based ELISA analysis of 370 sera samples collected from 11 penguins during three consecutive seasons of Spring (March to May), Summer (June to August) and Fall (September to November). (A) ELISA absorbance readings for the 370 sera samples collected from Spring to Fall are arranged in ascending order. Time of collection is indicated by color. Light grey represents Spring, dark grey represents Summer, and black represents Fall. Black dashed line indicates the single cut-off point (0.488) determined by change-point analysis. (B) Left: percentage of positive (A405 ≥ 0.488) and negative (A405 <0.488) sera samples; Right: distribution of positive samples in Spring (March to May), Summer (June to August), and Fall (September to November). (C) Percentage of penguin sera samples that tested positive (A405> = 0.488) in each month from March to November.

opencc-by-4.0Dec 2022View details →

Fig. 5. P. relictum MSP-1 in Plasmodium relictum MSP-1 capture antigen-based ELISA for detection of avian malaria antibodies in African penguins (Spheniscus demersus)

Fig. 5. P. relictum MSP-1 capture antigen-based ELISA analysis of test sera from penguins. Sera samples (370 total) from eleven penguins collected from Spring through Fall season were used as test samples in the assay to determine anti-P. relictum antibodies level. Light grey, dark grey, and black columns represent penguin sera samples collected in Spring, Summer, and Fall, respectively. Panel A–K represents ELISA results for individual penguins' sera collected at different time points from Spring to Fall. Panel L represents average ELISA absorbances for all 11 penguins at different sampling points. Each sample was assayed in triplicate, and the data shown represent means of three independent experiments with standard error bars.

opencc-by-4.0Aug 2024View details →

Detection of novel P. falciparum haplotypes under treatment pressure in pediatric severe malaria

The dataset contains Amplicon sequencing data targeting three Plasmodium falciparum polymorphic markers—cpmp, cpp, and ama1. These markers were analyzed to investigate the association between parasite clearance rate and the multiplicity of infection in Beninese children undergoing treatment for severe malaria.

opencc-by-4.0Oct 2024View details →

A scalable CRISPR-Cas9 gene editing system facilitates CRISPR screens in the malaria parasite Plasmodium berghei - sequencing data

This holds raw sequencing data, and extracted sgRNA counts

opencc-by-4.0Jun 2021View details →

Evaluation of different deployment strategies for larviciding to control malaria – a simulation study

Simulation datasets for: "Evaluation of different deployment strategies for larviciding to control malaria – a simulation study". The folders include a description folder with relevant input files for simulations in OpenMalaria and the processedExpResults includes the Rdataframes, generated from the raw simulation outputs, used for analysis.

opencc-by-4.0Jul 2021View details →

Simulation Results Data for 'Modelling new insecticide-treated bed nets for malaria-vector control: How to strategically manage resistance?'

GENERAL INFORMATION 1. Title of Dataset: Simulation Results Data for 'Modelling new insecticide-treated bed-nets for malaria-vector control: How to strategically manage resistance?' 2. Author Information     A. Investigator Contact Information         Name: Philip G. Madgwick         Institution: Syngenta          Address: Jealott’s Hill International Research Centre, Bracknell, RG42 6EY, UK         Email: philip.madgwick@syngenta.com     B. Investigator Contact Information         Name: Ricardo Kanitz         Institution: Syngenta          Address: Syngenta Crop Protection, Rosentalstrasse 67, CH-4058 Basel, Switzerland         Email: ricardo.kanitz@syngenta.com 3. Date of data collection (single date, range, approximate date): 2021-01-13 to 2021-02-01  4. Geographic location of data collection: UK  5. Information about funding sources that supported the collection of the data:  This work was conducted during a postdoctoral research position for PGM funded by the Innovative Vector Control Consortium (IVCC). SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: NA 2. Links to publications that cite or use the data: [UPDATE] 3. Links to other publicly accessible locations of the data: NA 4. Links/relationships to ancillary data sets: NA 5. Was data derived from another source? No 6. Recommended citation for this dataset: [UPDATE] DATA & FILE OVERVIEW 1. File List:  PSData_random6.csv - 10^6 random samples of each of the 17 parameters in the model, where rows are samples and columns are parameters (with column names corresponding to the parameters identified in the rows of Table 1 of the manuscript; see also DATA-SPECIFIC INFORMATION) Data_random6_maxpsMixture_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k=1; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_maxpsMixture_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k=1; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_maxpsMixture_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k=1; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Mixture_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_Mixture_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Mixture_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Mosaic_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used at 50% frequency each as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_Mosaic_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used at 50% frequency each as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Mosaic_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used at 50% frequency each as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Rotation_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_Rotation_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Rotation_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Rotation_Fixed_revmm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_Rotation_Fixed_revmn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_Rotation_Fixed_revnn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_SoloA_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_SoloA_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_SoloA_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   Data_random6_SoloB_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_SoloB_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has mitochondrial inheritance   Data_random6_SoloB_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance   2. Relationship between files, if important:  Files are named in accordance with the variables that describe each simulation setup, as described above. Each simulation dataset has 10^6 runs that correspond to the 10^6 random samples of each of the 17 parameters in the model in 'PSData_random6.csv'. 3. Additional related data collected that was not included in the current data package: NA 4. Are there multiple versions of the dataset? No METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Data were collected using Simulator.R, which is in the vignettes of the 'detsims' R package that accompanies the manuscript.  2. Methods for processing the data: Data were processed using Figures.R, which is in the vignettes of the 'detsims' R package that accompanies the manuscript.  3. Instrument- or software-specific information needed to interpret the data: Analysis was conducted in R version 4.0.3 (2020-10-10), using R packages identified in Figures.R, which is in the vignettes of the 'detsims' R package that accompanies the manuscript.  4. Standards and calibration information, if appropriate: NA 5. Environmental/experimental conditions: NA 6. Describe any quality-assurance procedures performed on the data: NA 7. People involved with sample collection, processing, analysis and/or submission: NA  DATA-SPECIFIC INFORMATION FOR: PSData_random6.csv 1. Number of variables:  17 variables with column names that have the following parameter meanings (see Table 1 in the manuscript):  Population Size    = N = starting population size (and carrying capacity in logistic model); random sample range on log-scale: 10^2 - 10^9 Intrinsic Birth Rate = b = % population growth rate (in logistic model); random sample following a standard log-normal distribution with mean=0 and sd=1 Intrinsic Death Rate = d = % breeding mosquitoes that die into next generation; random sample range: 0 - 1 Female Exposure    = x_[female-symbol] = % female mosquitoes that receive a dose; random sample range: 0 - 1 Male Exposure x_[male-symbol] = % male mosquitoes that receive a dose; random sample range: 0 - 1 Initial Frequency A = f_0,A = starting frequency of allele A; random sample range on log-scale: 10^-9 - 10^-2, limited to be within the range 1/N - N/100 where N is Population Size Effectiveness 1    = m_1 = % dosed mosquitoes that die from insecticide 1; random sample range: 0 - 1 Resistance Restoration A = r_A = % return to baseline fitness with resistance allele A; random sample range: 0 - 1 Dominance of Resistance Restoration A = h^r_A = % resistance restoration in heterozygote with allele A; random sample range: 0 - 1 Resistance Cost A = c_A = % non-dosed mosquitoes that die from carrying allele A; random sample range on log-scale: 10^-3 - 10^-0.5 Dominance of Resistance Cost A = h^c_A = % resistance cost in heterozygote with allele A; random sample range: 0 - 1 Initial Frequency B = f_0,B = starting frequency of allele B; random sample range on log-scale: 10^-9 - 10^-2, limited to be within the range 1/N - N/100 where N is Population Size Effectiveness 2    = m_2 = % dosed mosquitoes that die from insecticide 2; random sample range: 0 - 1 Resistance Restoration B = r_B = % return to baseline fitness with resistance allele B; random sample range: 0 - 1 Dominance of Resistance Restoration B = h^r_B = % resistance restoration in heterozygote with allele B; random sample range: 0 - 1 Resistance Cost B = c_B = % non-dosed mosquitoes that die from carrying allele B; random sample range on log-scale: 10^-3 - 10^-0.5 Dominance of Resistance Cost B = h^c_B = % resistance cost in heterozygote with allele B; random sample range: 0 - 1 2. Number of cases/rows:  10^6, corresponding to the number of random samples  3. Variable List: NA  4. Missing data codes: NA 5. Specialized formats or other abbreviations used: NA DATA-SPECIFIC INFORMATION FOR: all other dataset files (e.g. Data_random6_maxpsMixture_Fixed_mm.csv)  1. Number of variables:  10 variables with column names that have the following meanings: A_t_50% = the recorded number of generations that it takes for resistance allele A to reach >50% frequency; 0 means that resistance allele A never reaches >50% frequency   A_f_250 = the frequency of resistance allele A at the 250th generation  A_f_bar = the mean frequency of resistance allele A over the first 250 generations   B_t_50% = the recorded number of generations that it takes for resistance allele B to reach >50% frequency; 0 means that resistance allele B never reaches >50% frequency   B_f_250 = the frequency of resistance allele B at the 250th generation  B_f_bar = the mean frequency of resistance allele B over the first 250 generations  nf_80% = the recorded number of generations that it takes for the female population size to recover to >80% of its original size in the 0th generation; 0 means that the female population size never reaches >80% recovery; 1 means that the female population size never drops below 80% of its original size in the 1st generation nf_250 = the female population size at the 250th generation nf_bar = the mean female population size over the first 250 generations  nf_ext = the recorded number of generations that it takes for the female population size to drop below 1 (i.e. population extinction); 0 means that female population size never reaches <1 2. Number of cases/rows:  10^6, corresponding to the number of random samples  3. Variable List: NA 4. Missing data codes: all missing data is recorded as 0  5. Specialized formats or other abbreviations used: NA

opencc-by-4.0Dec 2022View details →

Malaria Parasite of Romanowsky-stained thick blood smears.

We label 1000 Romanowsky-stained thick blood smear images previously used in actual diagnoses. This dataset has 1.000 Romanowsky-stained thick blood smear images from the INS (National Institute of Health in Colombia). The photographic records came from 100 thick blood smears (10 images of different fields per slide). There were 217 and 783 images of good quality and bad quality, respectively. Of these, 702 images were with the presence of parasites and 298 without parasites. A total of 6188 parasites (Trophozoites - 5927, Squizonts - 114, Gametocytes - 147) were labeled, whose height and width varied from 13 to 138 pixels. Each image with parasites included from one to ninety parasites, with an average of eight per image. In addition, there were 12.712 leukocytes in all the images, whose height and width varied from 15 to 222 pixels, and only in twelve of the images were no leukocytes found.

opencc-by-4.0Dec 2021View details →

The MALaria Spatio-temporal Wind-Outbreak Trajectories Simulation (MALSWOTS)

A mechanistic-stochastic algorithm to identify clusters of super-spreader houses and their related stable hotspots by accounting for mosquito flight capabilities and the spatial configuration of malaria infections at the house level.

opencc-by-4.0Sep 2023View details →

Malaria drives unique regulatory responses across multiple immune cells during human infection

To investigate malaria driven transcriptional changes in specific immune cell subsets, we sorted live PBMCs from 6 malaria infected donors (day 0), and two subsequent time points after drug treatment (day 7 and 28), along with PBMCs from 2 healthy controls. We performed scRNAseq of these cells, and used clustering and sub-clustering to identify specific immune cell subsets. Differential gene analysis between day 0 and day 28 was performed for each cell cluster and sub-cluster. Key transcriptional changes were confirmed at the protein level with additional donor samples.

Study to Investigate the Clinical and Parasiticidal Activity and Pharmacokinetics of Different Doses of Artefenomel and Ferroquine in Patients With Uncomplicated Plasmodium Falciparum Malaria

ClinicalTrials.gov study NCT03660839. IPD Sharing: YES. Countries: 5. Publications: 1.

To Evaluate the Efficacy, Safety, Tolerability and Pharmacokinetics of a Single Dose Regimen of Ferroquine and Artefenomel in Adults and Children With Uncomplicated Plasmodium Falciparum Malaria

ClinicalTrials.gov study NCT02497612. IPD Sharing: YES. Countries: 7. Publications: 1.

Safety of KAE609 in Adults With Uncomplicated Plasmodium Falciparum Malaria.

ClinicalTrials.gov study NCT03334747. IPD Sharing: YES. Countries: 5. Publications: 2.

Efficacy, Safety and Tolerability of KAF156 in Combination With Lumefantrine Solid Dispersion Formulation (LUM-SDF) in Pediatric Population With Uncomplicated Plasmodium Falciparum Malaria

ClinicalTrials.gov study NCT04546633. IPD Sharing: YES. Countries: 5. Publications: 1.

Efficacy and Safety of KAF156 in Combination With LUM-SDF in Adults and Children With Uncomplicated Plasmodium Falciparum Malaria

ClinicalTrials.gov study NCT03167242. IPD Sharing: YES. Countries: 9. Publications: 2.

Pharmacokinetics, Safety, Tolerability and Efficacy of a New Artemether-lumefantrine Dispersible Tablet in Infants and Neonates <5 kg Body Weight With Acute Uncomplicated Plasmodium Falciparum Malaria

ClinicalTrials.gov study NCT04300309. IPD Sharing: YES. Countries: 2. Publications: 1.

Repeat Ivermectin Mass Drug Administrations for MALaria Control II

ClinicalTrials.gov study NCT03967054. IPD Sharing: YES. Countries: 1. Publications: 2.

publicSep 2014View details →

Data from: Individual genetic diversity and probability of infection by avian malaria parasites in blue tits (Cyanistes caeruleus)

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publicAug 2025View details →

Data from: Clone tracking through repeated malaria reveals high-fidelity CD4+ memory responses

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publicMar 2025View details →

Data from: Behavioural infection tolerance of malaria is negatively correlated with pro-inflammatory cytokine expression in the brain of an invasive songbird

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