Malaria risk can vary markedly between households in the same village, or between villages, but the determinants of this “micro-epidemiological” variation in malaria risk remain poorly understood. This study aimed to identify factors that explain fine-scale variation in malaria risk across settings and improve definitions and methods for malaria micro-epidemiology. A systematic review of studies that examined risk factors for variation in malaria infection between individuals, households, clusters, hotspots, or villages in any malaria-endemic setting was conducted. Four databases were searched for studies published up until 6th October 2015. Crude and adjusted effect estimates for risk factors for malaria infection were combined in random effects meta-analyses. Bias was assessed using the Newcastle–Ottawa Quality Assessment Scale. From 743 retrieved records, 51 studies were selected, representing populations comprising over 160,000 individuals in 21 countries, in high- and low-endemicity settings. Sixty-five risk factors were identified and meta-analyses were conducted for 11 risk factors. Most studies focused on environmental factors, especially increasing distance from a breeding site (OR 0.89, 95% CI 0.86–0.92, 10 studies). Individual bed net use was protective (OR 0.63, 95% CI 0.52–0.77, 12 studies), but not household bed net ownership. Increasing household size (OR 1.08, 95% CI 1.01–1.15, 4 studies) and household crowding (OR 1.79, 95% CI 1.48–2.16, 4 studies) were associated with malaria infection. Health seeking behaviour, medical history and genetic traits were less frequently studied. Only six studies examined whether individual-level risk factors explained differences in malaria risk at village or hotspot level, and five studies reported different risk factors at different levels of analysis. The risk of bias varied from low to high in individual studies. Insufficient reporting and comparability of measurements limited the number of meta-analyses conducted. Several variables associated with individual-level malaria infection were identified, but there was limited evidence that these factors explain variation in malaria risk at village or hotspot level. Social, population and other factors may confound estimates of environmental risk factors, yet these variables are not included in many studies. A structured framework of malaria risk factors is proposed to improve study design and quality of evidence in future micro-epidemiological studies.

Tegumentary leishmaniasis (TL) is a disease of skin and/or mucosal tissues caused by Leishmania parasites. TL patients may concurrently carry other pathogens, which may influence the clinical outcome of TL. This review focuses on the frequency of TL coinfections in human populations, interactions between Leishmania and other pathogens in animal models and human subjects, and implications of TL coinfections for clinical practice. For the purpose of this review, TL is defined as all forms of cutaneous (localised, disseminated, or diffuse) and mucocutaneous leishmaniasis. Human immunodeficiency virus (HIV) coinfection, superinfection with skin bacteria, and skin manifestations of visceral leishmaniasis are not included. We searched MEDLINE and other databases and included 73 records: 21 experimental studies in animals and 52 studies about human subjects (mainly cross-sectional and case studies). Several reports describe the frequency of Trypanosoma cruzi coinfection in TL patients in Argentina (about 41%) and the frequency of helminthiasis in TL patients in Brazil (15% to 88%). Different hypotheses have been explored about mechanisms of interaction between different microorganisms, but no clear answers emerge. Such interactions may involve innate immunity coupled with regulatory networks that affect quality and quantity of acquired immune responses. Diagnostic problems may occur when concurrent infections cause similar lesions (e.g., TL and leprosy), when different pathogens are present in the same lesions (e.g., Leishmania and Sporothrix schenckii), or when similarities between phylogenetically close pathogens affect accuracy of diagnostic tests (e.g., serology for leishmaniasis and Chagas disease). Some coinfections (e.g., helminthiasis) appear to reduce the effectiveness of antileishmanial treatment, and drug combinations may cause cumulative adverse effects. In patients with TL, coinfection is frequent, it can lead to diagnostic errors and delays, and it can influence the effectiveness and safety of treatment. More research is needed to unravel how coinfections interfere with the pathogenesis of TL. Infectious diseases are often studied one by one, but people can have more than one infection at the same time. This is likely to happen when different microorganisms are linked to specific geographical regions or living conditions. In this paper, we summarise the literature about infections occurring together with tegumentary leishmaniasis (TL), a disease of skin and mucosal tissues that is caused by Leishmania parasites. We found that in Latin America, patients with TL are often also infected with helminths or with Trypanosoma cruzi (the parasite that causes Chagas disease). Information from other parts of the world is scarce. Animal studies and observations in humans show that one infection can change the course of another infection, but how this happens is not well understood. When different infections affect the same patient at the same time, the diagnosis can be difficult, especially when different microorganisms are biologically similar, when they cause similar lesions, or when they are present in the same lesions. Treatment can also be difficult because some coinfections reduce the efficacy of the treatment against Leishmania and because some drug combinations can lead to cumulative adverse effects.

Background The rate of pulmonary tuberculosis (TB) recurrence is substantial. Identifying risk factors can support the development of prevention strategies. Methods We retrieved studies published between 1 January 1980 and 31 December 2022 that assessed factors associated with undifferentiated TB recurrence, relapse or reinfection. For factors reported in at least four studies, we performed random-effects meta-analysis to estimate a pooled relative risk (RR). We assessed heterogeneity, risk of publication bias and certainty of evidence. Results We included 85 studies in the review; 81 documented risk factors for undifferentiated recurrence, 17 for relapse and 10 for reinfection. The scope for meta-analyses was limited given the wide variety of factors studied, inconsistency in control for confounding and the fact that only few studies employed molecular genotyping. Factors that significantly contributed to moderately or strongly increased pooled risk and scored at least moderate certainty of evidence were: for undifferentiated recurrence, multidrug resistance (MDR) (RR 3.49; 95% CI 1.86 to 6.53) and fixed-dose combination TB drugs (RR 2.29; 95% CI 1.10 to 4.75) in the previous episode; for relapse, none; and for reinfection, HIV infection (RR 4.65; 95% CI 1.71 to 12.65). Low adherence to treatment increased the pooled risk of recurrence 3.3-fold (95% CI 2.37 to 4.62), but the certainty of evidence was weak. Conclusion This review emphasises the need for standardising methods for TB recurrence research. Actively pursuing MDR prevention, facilitating retention in treatment and providing integrated care for patients with HIV could curb recurrence rates. The use of fixed-dose combinations of TB drugs under field conditions merits further attention. PROSPERO registration number CRD42018077867.

In rural areas in Morocco, diagnosing cutaneous leishmaniasis (CL) can be challenging. We evaluated the accuracy of a rapid diagnostic test (RDT) based on antigen detection, CL Detect Rapid Test^™ (Inbios International Inc., Seattle, WA), in this setting. We consecutively recruited patients with new skin ulcers in nine primary health centers. We took a dental broach sample for the RDT and two other tissue samples by scraping the border and center of the lesion with a scalpel and smearing it on a slide. We duplicated each smear by pressing a clean slide against it and processed the slides by microscopy, polymerase chain reaction (PCR) internal transcribed spacer 1, and kDNA minicircle PCR. In a subgroup with positive PCR, the Leishmania species was identified using PCR-restriction fragment length polymorphism and PCR-sequencing of hsp70 genes. A participant with positive microscopy and/or PCR was considered a confirmed CL case. We computed sensitivity (Se) and specificity (Sp) of the RDT compared with this reference standard (ClinicalTrials.gov registration: NCT02979002). Between December 2016 and July 2017, we included 219 patients, 50% of them were under 18 years old. Rapid diagnostic test Se was 68% [95% confidence interval (CI): 61–74], Sp 94% [95% CI: 91–97], positive predictive value 95% [95% CI: 92–98], and negative predictive value 64% [95% CI: 58–70]. Despite its low Se, this novel RDT is a useful addition to clinical management of CL in Morocco, especially in isolated localities. Rapid diagnostic test–positive lesions can be treated as CL; but when RDT negative, microscopy should be done in a second step. The Se of the RDT can probably be optimized by improving the sampling procedure.

To estimate the diagnostic accuracy of HAT Sero K-SeT for the field diagnosis of second-stage human African trypanosomiasis (HAT). A phase III diagnostic accuracy design. Consecutive patients with symptoms clinically suggestive of HAT were prospectively enrolled. We compared results of the index test HAT Sero K-SeT with those of a composite reference standard: demonstration of trypanosomes in cerebrospinal fluid (CSF), or trypanosomes detected in any other body fluid AND white blood cell count in CSF >5/μl. Rural hospital in the Democratic Republic of the Congo. All patients above five years old presenting at Mosango hospital with a neurological problem of recent onset at the exclusion of trauma. n.a. Sensitivity and specificity of HAT Sero K-SeT test. The sensitivity of the HAT Sero K-SeT was 8/8 or 100.0% (95% confidence interval: 67.6 to 100.0%) and the specificity was 258/266 or 97.0% (94.2% to 98.5%). The high sensitivity of the HAT Sero K-SeT is in line with previously published estimates, though the sample of HAT cases in this study was small. The specificity estimate was very high and precise. This test, when negative, allows the clinician to rule out HAT in a clinical suspect in a hospital setting in this endemic region.