Estimating force of infection from serologic surveys with imperfect tests

Freedom from infection: enhancing decision-making for malaria elimination

Assessing elimination of malaria locally requires a surveillance system with high sensitivity and specificity to detect its presence without ambiguity. Currently, the WHO standard criteria of observing the absence of locally acquired cases for 3 consecutive years, combined with a health systems assessment, are used to justify claims of malaria elimination. However, relying on a qualitative framework to support the application of this guideline can lead to early, over-optimistic relaxation of control measures with the potential for resurgence. Overcoming this challenge requires innovative approaches to model the coupled processes of malaria transmission and its clinical observation.We propose a novel statistical framework based on a state-space model to probabilistically demonstrate the absence of malaria, using routinely collected health system data (which is extensive but inherently imperfect). By simultaneously modelling the expected malaria burden within the population and the probability of detection, we provide a robust estimate of the surveillance system's sensitivity and the corresponding probability of local elimination (probability of freedom from infection).Our study reveals a critical limitation of the traditional criterion for declaring malaria elimination, highlighting its inherent bias and potential for misinterpreting ongoing transmission. Such oversight not only misrepresents ongoing transmission but also places communities at risk for larger outbreaks. However, we demonstrate that our integrated approach to data comprehensively addresses this issue, effectively detecting ongoing transmission patterns, even when local reports might suggest otherwise.Our integrated framework has far-reaching implications for malaria control but also for infectious disease control in general. Our approach addresses the limitations of traditional criteria for declaring freedom from disease and opens the path to true optimisation of the allocation of limited resources. Our findings emphasise the urgent need to reassess existing methods to accurately confirm malaria elimination, and the importance of using comprehensive modelling techniques to continually monitor and maintain the effectiveness of current surveillance systems, enabling decisions grounded in quantitative evidence.

Burden of Chikungunya Virus Infection during an Outbreak in Myanmar

Chikungunya virus (CHIKV) infection is a re-emerging arboviral disease with no approved vaccine, although numerous options are in development. Before vaccine implementation, disease burden, affected age group, and hospitalization rate information should be documented. In 2019, a sizeable outbreak of the East Central South African genotype of CHIKV occurred in Myanmar, and during this period, a cross-sectional study was conducted in two regions, Mandalay and Yangon, to examine the molecular and seropositivity rate of the CHIKV infection. The participants (1124) included dengue-suspected pediatric patients, blood donors, and healthy volunteers, who were assessed using molecular assays (quantitative real-time RT-PCR), serological tests (anti-CHIKV IgM capture and IgG indirect enzyme-linked immunosorbent assays), and neutralization tests. The tests confirmed the following positivity rates: 11.3% (127/1124) for the molecular assay, 12.4% (139/1124) for the anti-CHIKV IgM Ab, 44.5% (500/1124) for the anti-CHIKV IgG Ab, and 46.3% (520/1124) for the CHIKV neutralizing Ab. The highest rate for the molecular test occurred with the dengue-suspected pediatric patients. The seroprevalence rate through natural infection was higher in the healthy volunteers and blood donors than that in the pediatric patients. The results of this study will help stakeholders determine the criteria for choosing appropriate recipients when a CHIKV vaccine is introduced in Myanmar.

Human and Livestock Surveillance Revealed the Circulation of Rift Valley Fever Virus in Agnam, Northern Senegal, 2021

The mosquito-borne disease caused by the Rift Valley Fever Virus (RVFV) is a viral hemorrhagic fever that affects humans and animals. In 1987, RVFV emerged in Mauritania, which caused the first RVFV outbreak in West Africa. This outbreak was shortly followed by reported cases in humans and livestock in Senegal. Animal trade practices with neighboring Mauritania suggest northern regions of Senegal are at high risk for RVF. In this study, we aim to conduct a molecular and serological survey of RVFV in humans and livestock in Agnam (northeastern Senegal) by RT-PCR (reverse transcription real-time polymerase chain reaction) and ELISA (Enzyme-Linked Immunosorbent Assay), respectively. Of the two hundred fifty-five human sera, one (0.39%) tested RVFV IgM positive, while fifty-three (20.78%) tested positive for RVFV IgG. For animal monitoring, out of 30 sheep recorded and sampled over the study period, 20 (66.67%) showed seroconversion to RVFV IgG antibodies, notably during the rainy season. The presence of antibodies increased significantly with age in both groups (p < 0.05), as the force of RVF infection (FOI), increased by 16.05% per year for humans and by 80.4% per month for livestock sheep. This study supports the usefulness of setting up a One Health survey for RVF management.

Crimean-Congo Hemorrhagic Fever Virus Survey in Humans, Ticks, and Livestock in Agnam (Northeastern Senegal) from February 2021 to March 2022

Crimean-Congo hemorrhagic fever virus (CCHFV) is widespread in Asia, Europe, and Africa. In Senegal, sporadic cases of CCHFV have been reported since 1960. Bordering Mauritania in northeastern Senegal, Agnam is an arid area in the region of Matam where CCHFV is endemic, which harbors a pastoralist community. Given the drought conditions of Agnam, inhabitants are in constant movement with their animals in search of pasture, which brings them into contact with pathogens such as arboviruses. To identify CCHFV in this area, we established a One Health site in order to analyze animal livestock, ticks and human samples collected over a one-year period by qRT-PCR and ELISA. Our analysis showed one (1/364) patient carried anti-CCHFV IgM and thirty-seven carried anti-CCHFV IgG (37/364). In livestock, anti-CCHFV IgG was detected in 13 (38.24%) of 34 sentinel sheep. The risk of CCHFV infection increased significatively with age in humans (p-value = 0.00117) and sheep (p-value = 1.18 × 10^-11). Additional risk factors for CCHFV infection in sheep were dry seasons (p-value = 0.004) and time of exposure (p-value = 0.007). Furthermore, we detected a total of three samples with CCHFV RNA within Rhipicephalus evertsi evertsi and Rhipicephalus guilhoni tick species. Our results highlighted the usefulness of a One Health survey of CCHFV in pastoral communities at risk of arboviruses.