A Smartphone App for Real-Time Assessment of Malaria Prophylaxis Adverse Events.

Background: Growth of international travel to malarial areas over the last decades has contributed to more travelers taking malaria prophylaxis. Travel-related symptoms may be wrongly attributed to malaria prophylaxis and hinder compliance. Here, we aimed to assess the frequency of real-time reporting of symptoms by travelers following malaria prophylaxis using a smartphone app. Method: Adult international travelers included in this single-center study (Barcelona, Spain) used the smartphone Trip Doctor® app developed by our group for real-time tracking of symptoms and adherence to prophylaxis. Results: Six hundred four (n = 604) international travelers were included in the study; 74.3% (449) used the app daily, and for one-quarter of travelers, malaria prophylaxis was prescribed. Participants from the prophylaxis group traveled more to Africa (86.7% vs. 4.3%; p < 0.01) and to high travel medical risk countries (60.8% vs. 18%; p < 0.01) and reported more immunosuppression (30.8% vs. 23.1% p < 0.01). Regarding symptoms, no significant intergroup differences were observed, and no relationship was found between the total number of malarial pills taken and reported symptoms. Conclusions: In our cohort, the number of symptoms due to malaria prophylaxis was not significantly higher than in participants for whom prophylaxis was not prescribed, and the overall proportion of symptoms is higher compared with other studies.

MALrisk: a machine-learning­based tool to predict imported malaria in returned travellers with fever

BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence could improve the management of febrile travellers. METHODS: Data from a multicentric prospective study of febrile travellers was obtained to build a machine-learning model to predict malaria cases among travellers presenting with fever. Demographic characteristics, clinical and laboratory variables were leveraged as features. Eleven machine-learning classification models were evaluated by 50-fold cross-validation in a Training set. Then, the model with the best performance, defined by the Area Under the Curve (AUC), was chosen for parameter optimization and evaluation in the Test set. Finally, a reduced model was elaborated with those features that contributed most to the model. RESULTS: Out of eleven machine-learning models, XGBoost presented the best performance (mean AUC of 0.98 and a mean F1 score of 0.78). A reduced model (MALrisk) was developed using only six features: Africa as a travel destination, platelet count, rash, respiratory symptoms, hyperbilirubinemia and chemoprophylaxis intake. MALrisk predicted malaria cases with 100% (95%CI 96-100) sensitivity and 72% (95%CI 68-75) specificity. CONCLUSIONS: The MALrisk can aid in the timely identification of malaria in non-endemic settings, allowing the initiation of empiric antimalarials and reinforcing the need for urgent transfer in healthcare facilities with no access to malaria diagnostic tests. This resource could be easily scalable to a digital application and could reduce the morbidity associated with late diagnosis.

Assessing viral metagenomics for the diagnosis of acute undifferentiated fever in returned travellers: a multicenter cohort study.

BACKGROUND: Up to 45% of febrile returning travellers remain undiagnosed after a thorough diagnostic work-up, even at referral centres. Although metagenomic next-generation sequencing (mNGS) has emerged as a promising tool, evidence of its usefulness in imported fever is very limited. METHODS: Travellers returning with fever were prospectively recruited in three referral clinics from November 2017 to November 2019. Unbiased mNGS optimised for virus detection was performed on serum samples of participants with acute undifferentiated febrile illness (AUFI), and results were compared to those obtained by reference diagnostic methods (RDM). RESULTS: Among 507 returned febrile travellers, 433(85.4%) presented with AUFI. Dengue virus (n = 86) and Plasmodium spp. (n = 83) were the most common causes of fever. 103/433(23.8%) AUFI remained undiagnosed at the end of the follow-up.Metagenomic next-generation sequencing unveiled potentially pathogenic microorganisms in 196/433(38.7%) AUFI. mNGS identifications were more common in patients with a shorter duration of fever (42.3% in ≤5 days vs 28.7% in >5 days, P = 0.005). Potential causes of fever were revealed in 25/103(24.2%) undiagnosed AUFI and 5/23(21.7%) travellers with severe undiagnosed AUFI. Missed severe aetiologies included eight bacterial identifications and one co-infection of B19 parvovirus and Aspergillus spp.Additional identifications indicating possible co-infections occurred in 29/316(9.2%) travellers with AUFI, and in 11/128(8.6%) travellers with severe AUFI, who had received a diagnosis through RDM. The most common co-infections detected in severe AUFI were caused by Gram-negative bacteria. Serum mNGS was unable to detect >50% of infectious diagnoses achieved by RDM and also yielded 607 non-pathogenic identifications. DISCUSSION: mNGS of serum can be a valuable diagnostic tool for selected travellers with undiagnosed AUFI or severe disease in addition to reference diagnostic techniques, especially during the first days of symptoms. Nevertheless, mNGS results interpretation presents a great challenge. Further studies evaluating the performance of mNGS using different sample types and protocols tailored to non-viral agents are needed.

Gut microbiota composition in travellers is associated with faecal lipocalin-2, a mediator of gut inflammation.

Introduction: We examined the gut microbiota of travellers returning from tropical areas with and without traveller's diarrhoea (TD) and its association with faecal lipocalin-2 (LCN2) levels. Methods: Participants were recruited at the Hospital Clinic of Barcelona, Spain, and a single stool sample was collected from each individual to perform the diagnostic of the etiological agent causing gastrointestinal symptoms as well as to measure levels of faecal LCN2 as a biomarker of gut inflammation. We also characterised the composition of the gut microbiota by sequencing the region V3-V4 from the 16S rRNA gene, and assessed its relation with the clinical presentation of TD and LCN2 levels using a combination of conventional statistical tests and unsupervised machine learning approaches. Results: Among 61 participants, 45 had TD, with 40% having identifiable etiological agents. Surprisingly, LCN2 levels were similar across groups, suggesting gut inflammation occurs without clinical TD symptoms. Differential abundance (DA) testing highlighted a microbial profile tied to high LCN2 levels, marked by increased Proteobacteria and Escherichia-Shigella, and decreased Firmicutes, notably Oscillospiraceae. UMAP analysis confirmed this profile's association, revealing distinct clusters based on LCN2 levels. The study underscores the discriminatory power of UMAP in capturing meaningful microbial patterns related to clinical variables. No relevant differences in the gut microbiota composition were found between travellers with or without TD. Discussion: The findings suggest a correlation between gut microbiome and LCN2 levels during travel, emphasising the need for further research to discern the nature of this relationship.

Not all severe malaria cases are severe: Is it time to redefine severity criteria for malaria in non-endemic regions?

BACKGROUND: The current definition of severe malaria in non-endemic areas follows WHO criteria, which mainly target children in malaria-endemic areas, potentially misclassifying cases in non-endemic regions. We assessed the performance of a modified severe malaria classification criteria within our patient cohort. METHODS: A cohort study of patients managed for malaria in a non-endemic setting (2005-2023) was analyzed. We classified patients into severe malaria (SM) using WHO 2013 criteria except for hyperparasitemia, where 2 % threshold was applied. Patients with SM were distinguished as very severe malaria (VSM) when presenting at least one of the following conditions: parasitemia >10 %, pulmonary edema, impaired consciousness, seizures, renal failure, metabolic acidosis or hyperlactatemia, shock or hypoglycemia. In patients with SM and no criteria for VSM, less severe malaria (LSM) was defined by: 2-10 % parasitemia, hyperbilirubinemia, prostration, anemia or minor bleeding. The primary composite outcome was death or the need for a life-saving intervention, as analyzed in the three comparative groups. Secondary outcome was the prevalence of co-infections. RESULTS: Among 506 patients with malaria, 176 (34.8 %) presented with SM. A total of 37 (7.3 %) patients developed a life-threatening condition, namely death (n = 4) and/or the need for life-saving interventions (n = 34). All fatalities and 33 out of the 34 life-saving interventions occurred in the VSM group. Patients in LSM group did not develop any life-threatening conditions. As to co-infections, 28 (5.5 %) patients had a community-acquired co-infection, with no differences between groups (p = 0.763). CONCLUSIONS: Severity criteria definitions would benefit from a review when assessing patients with malaria in non-endemic areas. Within the spectrum of SM, patients reclassified as LSM have a low risk of developing a life-threatening condition and present low co-infection incidence and could benefit from management out of intensive care units and a restrictive use of empirical antibiotics.

Consensus definitions in imported human schistosomiasis: a GeoSentinel and TropNet Delphi study.

Terminology in schistosomiasis is not harmonised, generating misunderstanding in data interpretation and clinical descriptions. This study aimed to achieve consensus on definitions of clinical aspects of schistosomiasis in migrants and returning travellers. We applied the Delphi method. Experts from institutions affiliated with GeoSentinel and TropNet, identified through clinical and scientific criteria, were invited to participate. Five external reviewers revised and pilot-tested the statements. Statements focusing on the definitions of acute or chronic; possible, probable, or confirmed; active; and complicated schistosomiasis were managed through REDCap and replies managed in a blinded manner. Round 1 mapped the definitions used by experts; subsequent rounds were done to reach consensus, or quantify disagreement, on the proposed statements. Data were analysed with percentages, medians, and IQRs of a 5-point Likert scale. The study was terminated on the basis of consensus or stability-related and time-related criteria. 28 clinicians and scientists met the criteria for experts. 25 (89%) of 28 experts replied to Round 1, 18 (64%) of 28 to Round 2, 19 (68%) of 28 to Round 3, and 21 (75%) of 28 to at least two rounds. High-level consensus (79-100% agreement and IQRs ≤1) was reached for all definitions. Consensus definitions will foster harmonised scientific and clinical communication and support future research and development of management guidelines for schistosomiasis.

Executive Summary of the Spanish Guidelines for the Diagnosis and Management of Imported Febrile Illnesses from the Spanish Society of Tropical Medicine and International Health (SEMTSI), the Imported Pathology Group of the Spanish Society of Infectious Diseases and Clinical Microbiology (GEPI-SEIMC), the Spanish Society of Family and Community Medicine (SEMFYC), the Spanish Society of Primary Care Physicians (SEMERGEN) and the Spanish Society of Emergency Medicine (SEMES).

The Spanish Society of Tropical Medicine and International Health (SEMTSI), the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), the Spanish Society of Emergency Medicine (SEMES), the Spanish Society of Primary Care Physicians (SEMERGEN) and the Spanish Society of Family and Community Medicine (SEMFYC) have prepared a consensus statement on the diagnosis and management of patients with imported febrile illnesses. Twenty authors with different backgrounds and representing different healthcare perspectives (ambulatory primary care, travel and tropical medicine specialists, emergency medicine, hospital care, microbiology and parasitology and public health), identified 39 relevant questions, which were organised in 7 thematic blocks. After a systematic review of the literature and a thoughtful discussion, the authors prepared 125 recommendations, as well as several tables and figures to be used as a consulting tool. The present executive summary shows a selection of some of the most relevant questions and recommendations included in the guidelines.

Epidemiology of Travel-Associated Dengue from 2007 to 2022: A GeoSentinel Analysis.

BACKGROUND: Dengue is a leading cause of febrile illness among international travellers. We aimed to describe the epidemiology and clinical characteristics of imported dengue in returning travellers evaluated at GeoSentinel sites from 2007-2022. METHODS: We retrieved GeoSentinel records of dengue among travellers residing in non-endemic countries. We considered dengue confirmed when diagnosed by a positive DENV-specific RT-PCR, positive NS-1 antigen, and/or anti-DENV IgG seroconversion, and probable when diagnosed by single anti-DENV IgM or high titre anti-DENV IgG detection. Severe dengue was defined as evidence of clinically significant plasma leakage or bleeding, organ failure, or shock, according to the 2009 WHO guidance. Complicated dengue was defined as either severe dengue or dengue with presence of any warning sign. Analyses were descriptive. RESULTS: This analysis included 5958 travellers with confirmed (n = 4859; 81.6%) or probable (n = 1099; 18.4%) dengue. The median age was 33 years (range: < 1-91); 3007 (50.5%) travellers were female. The median travel duration was 21 days (interquartile range [IQR]: 15-32). The median time between illness onset and GeoSentinel site visit was 7 days (IQR: 4-15). The most frequent reasons for travel were tourism (67.3%), visiting friends or relatives (12.2%), and business (11.0%). The most frequent regions of acquisition were Southeast Asia (50.4%), South-Central Asia (14.9%), the Caribbean (10.9%), and South America (9.2%). Ninety-five (1.6%) travellers had complicated dengue, of whom 27 (0.5%) had severe dengue, and one died. Of 2710 travellers with data available, 724 (26.7%) were hospitalized. The largest number of cases (n = 835) was reported in 2019. CONCLUSIONS: A broad range of international travellers should be aware of the risk of acquiring dengue and receive appropriate pretravel counselling regarding preventive measures. Prospective cohort studies are needed to further elucidate dengue risk by destination and over time, as well as severe outcomes and prolonged morbidity (long-dengue) due to travel-related dengue.