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Abstract Background To gain a deeper understanding of protective immunity against relapsing malaria, this study examined sporozoite-specific T cell responses induced by a chemoprophylaxis with sporozoite (CPS) immunization in a relapsing Plasmodium cynomolgi rhesus macaque model. Methods The animals received three CPS immunizations with P. cynomolgi sporozoites, administered by mosquito bite, while under two anti-malarial drug regimens. Group 1 (n = 6) received artesunate/chloroquine (AS/CQ) followed by a radical cure with CQ plus primaquine (PQ). Group 2 (n = 6) received atovaquone-proguanil (AP) followed by PQ. After the final immunization, the animals were challenged with intravenous injection of 104 P. cynomolgi sporozoites, the dose that induced reliable infection and relapse rate. These animals, along with control animals (n = 6), were monitored for primary infection and subsequent relapses. Immunogenicity blood draws were done after each of the three CPS session, before and after the challenge, with liver, spleen and bone marrow sampling and analysis done after the challenge. Results Group 2 animals demonstrated superior protection, with two achieving protection and two experiencing partial protection, while only one animal in group 1 had partial protection. These animals displayed high sporozoite-specific IFN-γ T cell responses in the liver, spleen, and bone marrow after the challenge with one protected animal having the highest frequency of IFN-γ+ CD8+, IFN-γ+ CD4+, and IFN-γ+ γδ T cells in the liver. Partially protected animals also demonstrated a relatively high frequency of IFN-γ+ CD8+, IFN-γ+ CD4+, and IFN-γ+ γδ T cells in the liver. It is important to highlight that the second animal in group 2, which experienced protection, exhibited deficient sporozoite-specific T cell responses in the liver while displaying average to high T cell responses in the spleen and bone marrow. Conclusions This research supports the notion that local liver T cell immunity plays a crucial role in defending against liver-stage infection. Nevertheless, there is an instance where protection occurs independently of T cell responses in the liver, suggesting the involvement of the liver's innate immunity. The relapsing P. cynomolgi rhesus macaque model holds promise for informing the development of vaccines against relapsing P. vivax.

Abstract Background Estimating malaria risk associated with work locations and travel across a region provides local health officials with information useful to mitigate possible transmission paths of malaria as well as understand the risk of exposure for local populations. This study investigates malaria exposure risk by analysing the spatial pattern of malaria cases (primarily Plasmodium vivax) in Ubon Ratchathani and Sisaket provinces of Thailand, using an ecological niche model and machine learning to estimate the species distribution of P. vivax malaria and compare the resulting niche areas with occupation type, work locations, and work-related travel routes. Methods A maximum entropy model was trained to estimate the distribution of P. vivax malaria for a period between January 2019 and April 2020, capturing estimated malaria occurrence for these provinces. A random simulation workflow was developed to make region-based case data usable for the machine learning approach. This workflow was used to generate a probability surface for the ecological niche regions. The resulting niche regions were analysed by occupation type, home and work locations, and work-related travel routes to determine the relationship between these variables and malaria occurrence. A one-way analysis of variance (ANOVA) test was used to understand the relationship between predicted malaria occurrence and occupation type. Results The MaxEnt (full name) model indicated a higher occurrence of P. vivax malaria in forested areas especially along the Thailand–Cambodia border. The ANOVA results showed a statistically significant difference between average malaria risk values predicted from the ecological niche model for rubber plantation workers and farmers, the two main occupation groups in the study. The rubber plantation workers were found to be at higher risk of exposure to malaria than farmers in Ubon Ratchathani and Sisaket provinces of Thailand. Conclusion The results from this study point to occupation-related factors such as work location and the routes travelled to work, being risk factors in malaria occurrence and possible contributors to transmission among local populations.

Abstract Background Although microscopy is a standard diagnostic tool for malaria and the gold standard, it is infrequently used because of unavailability of laboratory facilities and the absence of skilled readers in poor resource settings. Malaria rapid diagnostic tests (RDT) are currently used instead of or as an adjunct to microscopy. However, at very low parasitaemia (usually

IntroductionInternal and external quality control (QC) of rapid diagnostic tests (RDTs) is important to increase reliability of RDTs currently used to diagnose malaria. However, cross-checking of used RDTs as part of quality assurance can rarely be done by off-site personnel because there is no guarantee of retaining visible test lines after manufacturers' recommended reading time. Therefore, this study examined the potential of using Fionet™ technology for remote RDT quality monitoring at seven clinics, identifying reasons for making RDT processing and interpretation errors, and taking corrective actions for improvement of diagnosis and consequently improved management of febrile patients.MethodsThe study was conducted at seven military health facilities in Mainland Tanzania and utilized RDTs capable of detecting Plasmodium falciparum specific Histidine-rich protein 2 (Pf-HRP2) and the genus specific Plasmodium lactate dehydrogenase (pLDH) for other species of plasmodium (P. vivax, P. malariae or P. ovale; pan-pLDH). Patients' data and images of processed RDTs from seven clinics were uploaded on a Fionet web portal and reviewed regularly to monitor preparation procedures and visual interpretation of test results compared to automated analysis using the Deki reader of RDT. Problems detected were rapidly communicated to remote laboratory personnel at the clinic for corrective action and follow-up of patients who were falsely diagnosed as negative and missed treatment. Factors contributing to making errors in visual interpretation of RDT results were analyzed during visits to the health facilities.ResultsA total of 1,367 (1.6%) out of 83,294 RDT test images uploaded to the Fionet portal had discordant test results of which 822 (60.1%) and 545 (39.9%) were falsely reported as negative and positive, respectively. False negative and false positive test results were common for a single test line in 515 (62.7%) and 741 (54.2%) tests, respectively. Out of 1,367 RDT images assessed, 98 (7.2%) had quality problems related to preparation procedures of which 95(96.9%) errors were due to putting too much blood on the sample well or insufficient buffer in the respective wells. The reasons for discrepant results included, false reporting of none existent lines in 526 (38.5%) tests, missing a faint positive line in 493 (36.1%), missing a strong positive line in 248(18.1%) and errors caused by poorly processed RDTs in 96 (7.2%) tests. Among the false negative tests (n = 822), 669 (48.9%) patients were eligible for follow-up and only 339 (48.5%) were reached and 291 (85.8%) received appropriate anti-malaria therapy.ConclusionFionet technology enabled remote monitoring of RDT quality issues, identifying reasons contributing to laboratory personnel making errors and provided a rapid method to implement corrective actions at remote sites to improve malaria diagnosis and consequently improved health care management of febrile patients infected with malaria.