Hepatitis D double reflex testing of all hepatitis B carriers in low-HBV- and high-HBV/HDV-prevalence countries.

Hepatitis D virus (HDV) infection occurs as a coinfection with hepatitis B and increases the risk of hepatocellular carcinoma, decompensated cirrhosis, and mortality compared to hepatitis B virus (HBV) monoinfection. Reliable estimates of the prevalence of HDV infection and disease burden are essential to formulate strategies to find coinfected individuals more effectively and efficiently. The global prevalence of HBV infections was estimated to be 262,240,000 in 2021. Only 1,994,000 of the HBV infections were newly diagnosed in 2021, with more than half of the new diagnoses made in China. Our initial estimates indicated a much lower prevalence of HDV antibody (anti-HDV) and HDV RNA positivity than previously reported in published studies. Accurate estimates of HDV prevalence are needed. The most effective method to generate estimates of the prevalence of anti-HDV and HDV RNA positivity and to find undiagnosed individuals at the national level is to implement double reflex testing. This requires anti-HDV testing of all hepatitis B surface antigen-positive individuals and HDV RNA testing of all anti-HDV-positive individuals. This strategy is manageable for healthcare systems since the number of newly diagnosed HBV cases is low. At the global level, a comprehensive HDV screening strategy would require only 1,994,000 HDV antibody tests and less than 89,000 HDV PCR tests. Double reflex testing is the preferred strategy in countries with a low prevalence of HBV and those with a high prevalence of both HBV and HDV. For example, in the European Union and North America only 35,000 and 22,000 cases, respectively, will require anti-HDV testing annually.

Detection of Herpesvirus, Enterovirus, and Arbovirus infection in patients with suspected central nervous system viral infection in the Western Brazilian Amazon.

Acute infections of the central nervous system (CNS) can be caused by various pathogens. In this study, the presence of herpesviruses (HHV), enteroviruses (EVs), and arboviruses were investigated in CSF samples from 165 patients with suspected CNS viral infection through polymerase chain reaction (PCR) and reverse transcriptase PCR. The genomes of one or more viral agents were detected in 29.7% (49/165) of the CSF samples. EVs were predominant (16/49; 32.6%) followed by Epstein-Barr virus (EBV) (22.4%), Varicella-Zoster virus (VZV) (20.4%), Cytomegalovirus (CMV) (18.4%), herpes simplex virus (HSV-1) (4.1%), (HSV-2) (4.1%), and the arboviruses (14.3%). Four of the arboviruses were of dengue virus (DENV) and three of oropouche virus (OROV). The detection of different viruses in the CNS of patients with meningitis or encephalitis highlight the importance of maintaining an active laboratory monitoring diagnostics with rapid methodology of high sensitivity in areas of viral hyperendemicity that may assist in clinical decisions and in the choice of antiviral therapy.

Mayaro virus infection in amazonia: a multimodel inference approach to risk factor assessment.

BACKGROUND: Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data--particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment. METHODOLOGY/PRINCIPAL FINDINGS: A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (ß ± SE) on which to base inference. Residence area (ß(Village)  =  2.93 ± 0.41; ß(Upland) = -0.56 ± 0.33, ß(Riverbanks)  =  -2.37 ± 0.55) and bednet use (ß = -0.95 ± 0.28) were the most important factors, followed by crop-plot ownership (ß  =  0.39 ± 0.22) and regular use of a closed toilet/latrine (ß = 0.19 ± 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. CONCLUSIONS/SIGNIFICANCE: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.