Background In the absence of definitive diagnosis, healthcare providers are likely to prescribe empirical antibacterials to those who test negative for malaria. This problem is of critical importance in Southern Asia (SA) and South-eastern Asia (SEA) where high levels of antimicrobial consumption and high prevalence of antimicrobial resistance have been reported. To improve management and guide further diagnostic test development, better understanding is needed of the true causative agents of fever and their geographical variability. Methods We conducted a systematic review of published literature (1980–2015) to characterise the spectrum of pathogens causing non-malarial febrile illness in SA and SEA. We searched six databases in English and French languages: MEDLINE, EMBASE, Global Health (CABI) database, WHO Global Health Library, PASCAL, and Bulletin de la Société Française de Parasitologie (BDSP). Selection criteria included reporting on an infection or infections with a confirmed diagnosis, defined as pathogens detected in or cultured from samples from normally sterile sites, or serological evidence of current or past infection. Results A total of 29,558 records from 19 countries in SA and SEA were screened, of which 2410 (8.1%) met the selection criteria. Bacterial aetiologies were reported in 1235 (51.2%) articles, viral in 846 (35.1%), parasitic in 132 (5.5%), and fungal in 54 (2.2%), and 143 (6.0%) articles reported more than one pathogen group. In descending order of frequency, Salmonella Typhi, Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and coagulase negative Staphylococcus were the commonly reported bacteria, while dengue virus, chikungunya virus, Japanese encephalitis virus, hepatitis B virus, and hepatitis C virus were common viral pathogens reported. Reports of rarely reported or emerging pathogens included a case report of Borrelia burgdorferi (Lyme disease) in India in 2010 and reports of Nipah virus in Singapore and India. Conclusions This review summarises the reported non-malaria pathogens that may cause febrile illness in SA and SEA. The findings emphasise the need of standardising the reporting of aetiological studies to develop effective, evidence-based fever management and improved surveillance. Research and development of diagnostic tools would benefit from up-to-date epidemiological reporting of the regional diversities of non-malaria fever aetiologies. Trial registration PROSPERO registration, CRD42016049281

Background: Many available medicines have been evaluated as potential repurposed treatments for coronavirus disease 2019 (COVID-19). We summarise the registered study landscape for 32 priority pharmacological treatments identified following consultation with external experts of the COVID-19 Clinical Research Coalition. Methods: All eligible trial registry records identified by systematic searches of the World Health Organisation International Clinical Trials Registry Platform as of 26th May 2021 were reviewed and extracted. A descriptive summary of study characteristics was performed. Results: We identified 1,314 registered studies that included at least one of the 32 priority pharmacological interventions. The majority (1,043, 79%) were randomised controlled trials (RCTs). The sample size of the RCTs identified was typically small (median (25th, 75th percentile) sample size = 140 patients (70, 383)), i.e. individually powered only to show very large effects. The most extensively evaluated medicine was hydroxychloroquine (418 registered studies). Other widely studied interventions were convalescent plasma (n=208), ritonavir (n=189) usually combined with lopinavir (n=181), and azithromycin (n=147). Very few RCTs planned to recruit participants in low-income countries (n=14; 1.3%). A minority of studies (348, 26%) indicated a willingness to share individual participant data. The living systematic review data are available at https://iddo.cognitive.city Conclusions: There are many registered studies planning to evaluate available medicines as potential repurposed treatments of COVID-19. Most of these planned studies are small, and therefore substantially underpowered for most relevant endpoints. Very few are large enough to have any chance of providing enough convincing evidence to change policies and practices. The sharing of individual participant data (IPD) from these studies would allow pooled IPD meta-analyses which could generate definitive conclusions, but most registered studies did not indicate that they were willing to share their data.