Comprehensive data on the relative contribution of bacteremia to malaria outcomes in a large number of participants are lacking. Therefore, we collated data on the co-existence of malaria and bacteremia in the literature to provide evidence-based information for future studies investigating the clinical significance of this co-infection. The study protocol was registered at PROSPERO (ID: CRD42021287971). Relevant studies were identified from PubMed, Web of Science, and Scopus. The pooled prevalence of (1) co-existent malaria and bacteremia among febrile patients, (2) the pooled prevalence of bacteremia among patients with malaria, (3) the probability of co-infection, and (4) the pooled prevalence of deaths were estimated by the random-effects model. Fifty-one studies involving 1583 cases of co-infection were included in the analyses. Typhoidal Salmonella spp. and Staphylococcus aureus were the most common Gram-negative and Gram-positive bacteria, respectively. The prevalence of co-existent malaria and bacteremia among febrile patients was 1.9% (95% confidence interval (CI) = 1.5–2.2%, I² = 96.64%, 31 studies). The prevalence of bacteremia among patients with malaria was 7.6% (95% CI = 6.7–8.7%, and I² = 96.68%, 43 studies). Co-infection by malaria and bacteremia did not occur by chance (p = 0.024, odds ratio = 0.64, 95% CI = 0.43–0.94, and I² = 95.7%, 29 studies). The pooled prevalence of deaths among patients with co-infection was 15.0% (95% CI = 8.0–23.0%, I² = 75.23%, 8 studies). On the basis of this study, we conclude that although the prevalence of co-infection was low, patients with malaria appear at greater risk of bacteremia and death.

Background: The entomological inoculation rate (EIR) is one of the key indices used to evaluate malaria transmission and vector control interventions. One of the components of the EIR is the sporozoite rate in Anopheles vectors. A systematic review and meta-analysis was performed to identify the prevalence of Plasmodium spp. in field-collected Anopheles species across Thailand. Methods: This systematic review was registered under the PROSPERO number CRD42021297255. Studies that focused on the identification of Plasmodium spp. in Anopheles mosquitoes were identified from the electronic databases PubMed, Web of Science, and Scopus. The quality of the identified studies was determined using the Strengthening the Reporting of Observational Studies in Epidemiology approach. The proportion of Anopheles mosquitoes collected, Anopheles vectors for Plasmodium species, and specificity of Anopheles vectors for Plasmodium species were analyzed. The pooled prevalence of Plasmodium species among the primary vectors (Anopheles dirus, Anopheles minimus, and Anopheles maculatus) was estimated using the random-effects model. Results: Of the 1113 studies identified, 31 were included in the syntheses. Of the 100,910 Anopheles mosquitoes identified for species and sibling species, An. minimus (40.16%), An. maculatus (16.59%), and Anopheles epiroticus (9.18%) were the most prevalent Anopheles species. Of the 123,286 Anopheles mosquitoes identified, 566 (0.46%) were positive for Plasmodium species. The highest proportions of Plasmodium species were identified in Anopheles hodgkini (2/6, 33.3%), Anopheles nigerrimus (2/24, 8.33%), Anopheles balabacensis (4/84, 4.76%), An. dirus (114/4956, 2.3%), Anopheles annularis (16/852, 1.88%), Anopheles kochi (8/519, 1.54%), Anopheles vagus (3/215, 1.4%), and Anopheles baimaii (1/86, 1.16%). The pooled prevalence of Plasmodium species identified in the main Anopheles vectors was 0.4% of that of Plasmodium species identified in An. dirus was 2.1%, that of Plasmodium species identified in An. minimus was 0.4%, and that of Plasmodium species identified in An. maculatus was 0.4%. Conclusions: We found a low prevalence of Plasmodium infection in Anopheles mosquitoes across Thailand. Therefore, the use of EIR to determine the impact of vector control intervention on malaria parasite transmission and elimination in Thailand must be undertaken with caution, as a large number of Anopheles specimens may be required. Graphical

There are limited data regarding prevalence, anti-malarial chemoprophylaxis, and causes of death for severe imported malaria. Thus, we conducted a systematic review and meta-analysis to characterise these variables. We searched studies reporting deaths attributable to severe imported malaria. The following pooled prevalence rates were determined: 1) the pooled prevalence of severe malaria among patients with imported malaria, 2) the pooled prevalence of deaths among patients with severe imported malaria, 3) the pooled prevalence of anti-malarial chemoprophylaxis among patients with severe imported malaria, and 4) the causes of death among patients with severe imported malaria. The search identified 52 studies that were mainly conducted in Europe (25, 48.1%), North America (16, 30.8%) and Asia (7, 13.5%). The pooled prevalence of severe imported malaria was 12.5% (95% confidence interval [CI] = 10.3%-14.6%, I² = 99.32%, 12393 severe cases/118325 imported cases). The pooled prevalence of deaths attributable to severe imported malaria was 5.1% (95% CI = 4.0%-6.2%, I² = 91.72%, 721 deaths/16310 severe cases). The pooled prevalence of adequate anti-malarial chemoprophylaxis among patients with severe imported malaria was 9.7% (95% CI = 6.5%-13.0%, I² = 89.9%, 203/2049 cases). The most common cause of death was multi-organ failure (12.3%). The results highlighted the need for education and preventative measures for travellers, immigrants, or workers who plan to visit malaria-endemic areas to minimize the risk of severe disease or death.

Background: Co-infection with malaria and chikungunya could exert a significant public health impact with infection misdiagnosis. Therefore, this study aimed to collect qualitative and quantitative evidence of malaria and chikungunya co-infection among febrile patients. Methods : Potentially relevant studies were identified using PubMed, Web of Science, and Scopus. The bias risk of the included studies was assessed using the checklist for analytical cross-sectional studies developed by the Joanna Briggs Institute. The pooled prevalence of malaria and chikungunya co-infection among febrile patients and the pooled prevalence of chikungunya virus (CHIKV) infection among malaria patients were estimated with the random effect model. The odds of malaria and chikungunya co-infection among febrile patients were also estimated using a random effect model that presumed the heterogeneity of the outcomes of the included studies. The heterogeneity among the included studies was assessed using the Cochran Q test and I² statistics. Publication bias was assessed using the funnel plot and Egger’s test. Results : Of the 1924 studies that were identified from the three databases, 10 fulfilled the eligibility criteria and were included in our study. The pooled prevalence of malaria and chikungunya co-infection (182 cases) among febrile patients (16,787 cases), stratified by diagnostic tests for CHIKV infection, was 10% (95% confidence interval (CI): 8–11%, I²: 99.5%) using RDT (IgM), 7% (95% CI: 4–10%) using the plaque reduction neutralization test (PRNT), 1% (95% CI: 0–2%, I²: 41.5%) using IgM and IgG ELISA, and 4% (95% CI: 2–6%) using real-time RT-PCR. When the prevalence was stratified by country, the prevalence of co-infection was 7% (95% CI: 5–10%, I²: 99.5%) in Nigeria, 1% (95% CI: 0–2%, I²: 99.5%) in Tanzania, 10% (95% CI: 8–11%) in Sierra Leone, 1% (95% CI: 0–4%) in Mozambique, and 4% (95% CI: 2–6%) in Kenya. The pooled prevalence of CHIKV infection (182 cases) among malaria patients (8317 cases), stratified by diagnostic tests for CHIKV infection, was 39% (95% CI: 34–44%, I²: 99.7%) using RDT (IgM), 43% (95% CI: 30–57%) using PRNT, 5% (95% CI: 3–7%, I²: 5.18%) using IgM and IgG ELISA, and 9% (95% CI: 6–15%) using real-time RT-PCR. The meta-analysis showed that malaria and chikungunya co-infection occurred by chance (p: 0.59, OR: 0.32, 95% CI: 0.6–1.07, I²: 78.5%). Conclusions : The prevalence of malaria and chikungunya co-infection varied from 0% to 10% as per the diagnostic test for CHIKV infection or the country where the co-infection was reported. Hence, the clinicians who diagnose patients with malaria infections in areas where two diseases are endemic should further investigate for chikungunya co-infection to prevent misdiagnosis or delayed treatment of concurrent infection.

Procalcitonin (PCT), as a marker of malaria severity, remains to be investigated. The present study collated and compared the levels of PCT between patients with severe malaria, uncomplicated malaria, and control participants to assess their role in predicting malaria infection and disease severity. The systematic review was registered at PROSPERO with registration number CRD42021297243. The search for relevant studies that reported PCT in patients with malaria was performed in PubMed, Scopus, and Web of Science. The following meta-analyses were conducted; (1) the pooled mean PCT levels in patients with severe and uncomplicated malaria, and (2) the pooled mean difference in PCT levels between patients with severe and uncomplicated malaria. Fifteen studies were included for qualitative and quantitative syntheses. The meta-analysis results show that the pooled mean PCT levels in patients with uncomplicated malaria were 3.92 ng/mL (95% CI: 2.26–5.58 ng/mL, I²: 96.5, five studies), whereas the pooled mean PCT levels in patients with severe malaria were 14.13 ng/mL (95% CI: 8.75–19.5 ng/mL, I²: 92.6, six studies). The meta-analysis showed that patients with severe malaria had an equal mean of PCT compared to those with uncomplicated malaria when the random-effects model was used (p: 0.055, weighted mean difference: 6.93, 95% CI: −0.16–14.02, I²: 84.6%, four studies). There were probable correlations between the level of parasitemia, immunity level, and possibly bacterial or other parasitic co-infection that could affect the PCT level among different clinical severities of malaria. Therefore, the PCT level alone does not seem to be a suitable biomarker to discriminate the severe/uncomplicated or infected/uninfected cases. Further studies should investigate the increased PCT levels in combination with other markers in association with malaria infection and severity.

Malaria and leptospirosis are important cosmopolitan infections that have emerged with overlapping geographic distribution, especially in tropical and subtropical regions. Therefore, co-infection with malaria and leptospirosis may occur in overlapping areas. The present study aimed to quantify the prevalence of malaria and leptospirosis co-infection among febrile patients. The association between malaria and leptospirosis infections was also investigated. Relevant studies that had reported malaria and leptospirosis co-infection were identified from PubMed, Scopus, and Web of Science. The risk of bias of the studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Tool. The pooled prevalence of malaria and leptospirosis co-infections among febrile patients and the pooled prevalence of leptospirosis infection among malaria patients were estimated using random effect models. The association between malaria and leptospirosis infection among febrile patients was estimated using random effect models. The outcomes of each study were shown in a forest plot in point estimate and 95% confidence interval (CI). Heterogeneity among the included studies was assessed using Cochran’s Q and quantified using I-squared statistics. For leptospirosis, subgroup analyses of countries, diagnostic tests, and participants’ age groups were performed to specify prevalence in each subgroup. Publication bias was assessed by funnel-plot visualization. Of the 2370 articles identified from the databases, 15 studies met the eligibility criteria and were included for qualitative and quantitative syntheses. Most of the included studies were conducted in India (5/15, 33.3%), Thailand (3/15, 20%), and Cambodia (2/15, 13.3%). Most of the enrolled cases were febrile patients (5838 cases) and malaria-positive patients (421 cases). The meta-analysis showed that the pooled prevalence of malaria and leptospirosis co-infection (86 cases) among febrile patients was 1% (95% CI: 1–2%, I²: 83.3%), while the pooled prevalence of leptospirosis infection (186 cases) among malaria patients was 13% (95% CI: 9–18%, I²: 90.3%). The meta-analysis showed that malaria and leptospirosis co-infections occurred by chance (p: 0.434, OR: 1.4, 95% CI: 0.6–3.28, I²: 85.2%). The prevalence of malaria in leptospirosis co-infection among febrile patients in the included studies was low. Co-infection was likely to occur by chance. However, as clinical symptoms of leptospirosis patients were non-specific and not distinguishable from symptoms of malaria patients, clinicians caring for febrile patients in an area where those two diseases are endemic should maintain a high index of suspicion for both diseases and whether mono-infections or co-infections are likely. Recognition of this co-infection may play an important role in reducing disease severity and treatment duration.