An evaluation of the Zambia influenza sentinel surveillance system, 2011-2017

Comprehensive surveillance of acute respiratory infections during the COVID-19 pandemic: a methodological approach using sentinel networks, Castilla y León, Spain, January 2020 to May 2022

BackgroundSince 1996, epidemiological surveillance of acute respiratory infections (ARI) in Spain has been limited to seasonal influenza, respiratory syncytial virus (RSV) and potential pandemic viruses. The COVID-19 pandemic provides opportunities to adapt existing systems for extended surveillance to capture a broader range of ARI.AimTo describe how the Influenza Sentinel Surveillance System of Castilla y León, Spain was rapidly adapted in 2020 to comprehensive sentinel surveillance for ARI, including influenza and COVID-19.MethodsUsing principles and methods of the health sentinel network, we integrated electronic medical record data from 68 basic surveillance units, covering 2.6% of the regional population between January 2020 to May 2022. We tested sentinel and non-sentinel samples sent weekly to the laboratory network for SARS-CoV-2, influenza viruses and other respiratory pathogens. The moving epidemic method (MEM) was used to calculate epidemic thresholds.ResultsARI incidence was estimated at 18,942 cases per 100,000 in 2020/21 and 45,223 in 2021/22, with similar seasonal fold increases by type of respiratory disease. Incidence of influenza-like illness was negligible in 2020/21 but a 5-week epidemic was detected by MEM in 2021/22. Epidemic thresholds for ARI and COVID-19 were estimated at 459.4 and 191.3 cases per 100,000 population, respectively. More than 5,000 samples were tested against a panel of respiratory viruses in 2021/22.ConclusionExtracting data from electronic medical records reported by trained professionals, combined with a standardised microbiological information system, is a feasible and useful method to adapt influenza sentinel reports to comprehensive ARI surveillance in the post-COVID-19 era.

Influenza Virus: Tracking, Predicting, and Forecasting

Influenza is a common respiratory infection that causes considerable morbidity and mortality worldwide each year. In recent years, along with the improvement in computational resources, there have been a number of important developments in the science of influenza surveillance and forecasting. Influenza surveillance systems have been improved by synthesizing multiple sources of information. Influenza forecasting has developed into an active field, with annual challenges in the United States that have stimulated improved methodologies. Work continues on the optimal approaches to assimilating surveillance data and information on relevant driving factors to improve estimates of the current situation (nowcasting) and to forecast future dynamics.

Facility-based surveillance for influenza and respiratory syncytial virus in rural Zambia

BACKGROUND

While southern Africa experiences among the highest mortality rates from respiratory infections, the burden of influenza and respiratory syncytial virus (RSV) in rural areas is poorly understood.

METHODS

We implemented facility-based surveillance in Macha, Zambia. Outpatients and inpatients presenting with influenza-like illness (ILI) underwent testing for influenza A, influenza B, and RSV and were prospectively followed for 3 to 5 weeks to assess clinical course. Log-binomial models assessed correlates of infection and clinical severity.

RESULTS

Between December 2018 and December 2019, 17% of all outpatients presented with ILI and 16% of inpatients were admitted with an acute respiratory complaint. Influenza viruses and RSV were detected in 17% and 11% of outpatient participants with ILI, and 23% and 16% of inpatient participants with ILI, respectively. Influenza (July-September) and RSV (January-April) prevalence peaks were temporally distinct. RSV (relative risk [RR]: 1.78; 95% confidence interval [CI] 1.51-2.11), but not influenza, infection was associated with severe disease among patients with ILI. Underweight patients with ILI were more likely to be infected with influenza A (prevalence ratio [PR]: 1.72; 95% CI 1.04-2.87) and to have severe influenza A infections (RR: 2.49; 95% CI 1.57-3.93).

CONCLUSIONS

Populations in rural Zambia bear a sizeable burden of viral respiratory infections and severe disease. The epidemiology of infections in this rural area differs from that reported from urban areas in Zambia.

Attenuated infection by a Pteropine orthoreovirus isolated from an Egyptian fruit bat in Zambia

Background

Pteropine orthoreovirus (PRV) is an emerging bat-borne zoonotic virus that causes severe respiratory illness in humans. Although PRVs have been identified in fruit bats and humans in Australia and Asia, little is known about the prevalence of PRV infection in Africa. Therefore, this study performed an PRV surveillance in fruit bats in Zambia.

Methods

Egyptian fruit bats (Rousettus aegyptiacus, n = 47) and straw-colored fruit bats (Eidolon helvum, n = 33) captured in Zambia in 2017–2018 were screened for PRV infection using RT-PCR and serum neutralization tests. The complete genome sequence of an isolated PRV strain was determined by next generation sequencing and subjected to BLAST and phylogenetic analyses. Replication capacity and pathogenicity of the strain were investigated using Vero E6 cell cultures and BALB/c mice, respectively.

Results

An PRV strain, tentatively named Nachunsulwe-57, was isolated from one Egyptian fruit bat. Serological assays demonstrated that 98% of sera (69/70) collected from Egyptian fruit bats (n = 37) and straw-colored fruit bats (n = 33) had neutralizing antibodies against PRV. Genetic analyses revealed that all 10 genome segments of Nachunsulwe-57 were closely related to a bat-derived Kasama strain found in Uganda. Nachunsulwe-57 showed less efficiency in viral growth and lower pathogenicity in mice than another PRV strain, Miyazaki-Bali/2007, isolated from a patient.

Conclusions

A high proportion of Egyptian fruit bats and straw-colored fruit bats were found to be seropositive to PRV in Zambia. Importantly, a new PRV strain (Nachunsulwe-57) was isolated from an Egyptian fruit bat in Zambia, which had relatively weak pathogenicity in mice. Taken together, our findings provide new epidemiological insights about PRV infection in bats and indicate the first isolation of an PRV strain that may have low pathogenicity to humans.

Pteropine orthoreovirus (PRV) is a causative agent of acute respiratory illness in humans in tropical and sub-tropical regions in Southeast Asia. PRVs have been originally isolated from fruit bats, and it is assumed that PRVs spread to humans by both bat-to-human and human-to-human transmission. Recently, an PRV was also detected from a fruit bat in the Afrotropical region and might potentially cause an emerging infection of the bat-borne zoonotic virus in Africa. However, little is known about the prevalence of PRV infection in Africa. In this study, we demonstrated the high prevalence of PRV infection in bat populations in Zambia and isolated a new strain of PRV from Egyptian fruit bats. In addition, we found that the bat-derived PRV strain had lower pathogenicity in mice than a human-derived PRV strain isolated from a patient in Southeast Asia. Our findings provide new epidemiological information about PRV in fruit bats in the Afrotropical region and indicate the first isolation of an PRV strain that may cause attenuated infection in humans.

Performance of the Severe Acute Respiratory Illness Sentinel Surveillance System in Yemen: Mixed Methods Evaluation Study

Background

The national severe acute respiratory illness (SARI) surveillance system in Yemen was established in 2010 to monitor SARI occurrence in humans and provide a foundation for detecting SARI outbreaks.

Objective

To ensure that the objectives of national surveillance are being met, this study aimed to examine the level of usefulness and the performance of the SARI surveillance system in Yemen.

Methods

The updated Centers for Disease Control and Prevention guidelines were used for the purposes of our evaluation. Related documents and reports were reviewed. Data were collected from 4 central-level managers and stakeholders and from 10 focal points at 4 sentinel sites by using a semistructured questionnaire. For each attribute, percent scores were calculated and ranked as follows: very poor (≤20%), poor (20%-40%), average (40%-60%), good (60%-80%), and excellent (>80%).

Results

As rated by the evaluators, the SARI surveillance system achieved its objectives. The system’s flexibility (percent score: 86%) and acceptability (percent score: 82%) were rated as “excellent,” and simplicity (percent score: 74%) and stability (percent score: 75%) were rated as “good.” The percent score for timeliness was 23% in 2018, which indicated poor timeliness. The overall data quality percent score of the SARI system was 98.5%. Despite its many strengths, the SARI system has some weaknesses. For example, it depends on irregular external financial support.

Conclusions

The SARI surveillance system was useful in estimating morbidity and mortality, monitoring the trends of the disease, and promoting research for informing prevention and control measures. The overall performance of the SARI surveillance system was good. We recommend expanding the system by promoting private health facilities’ (eg, private hospitals and private health centers) engagement in SARI surveillance, establishing an electronic database at central and peripheral sites, and providing the National Central Public Health Laboratory with the reagents needed for disease confirmation.

First COVID-19 case in Zambia - Comparative phylogenomic analyses of SARS-CoV-2 detected in African countries

Since its first discovery in December 2019 in Wuhan, China, COVID-19, caused by the novel coronavirus SARS-CoV-2, has spread rapidly worldwide. While African countries were relatively spared initially, the initial low incidence of COVID-19 cases was not sustained for long due to continuing travel links between China, Europe and Africa. In preparation, Zambia had applied a multisectoral national epidemic disease surveillance and response system resulting in the identification of the first case within 48 h of the individual entering the country by air travel from a trip to France. Contact tracing showed that SARS-CoV-2 infection was contained within the patient’s household, with no further spread to attending health care workers or community members. Phylogenomic analysis of the patient’s SARS-CoV-2 strain showed that it belonged to lineage B.1.1., sharing the last common ancestor with SARS-CoV-2 strains recovered from South Africa. At the African continental level, our analysis showed that B.1 and B.1.1 lineages appear to be predominant in Africa. Whole genome sequence analysis should be part of all surveillance and case detection activities in order to monitor the origin and evolution of SARS-CoV-2 lineages across Africa.

Evaluation of a mobile health approach to improve the Early Warning System of influenza surveillance in Cameroon

Background

Rapid reporting of surveillance data is essential to better inform national prevention and control strategies.

Objectives

We compare the newly implemented smartphone‐based system to the former paper‐based and short message service (SMS) for collecting influenza epidemiological data in Cameroon.

Methods

Of the 13 sites which collect data from persons with influenza‐like illness (ILI), six sites send data through the EWS, while seven sites make use of the paper‐based system and SMS. We used four criteria for the comparison of the data collection tools: completeness, timeliness, conformity and cost.

Results

Regarding the different collection tools, data sent by the EWS were significantly more complete (97.6% vs 81.6% vs 44.8%), prompt (74.4% vs n/a vs 60.7%) and of better quality (93.7% vs 76.1% vs 84.0%) than data sent by the paper‐based system and SMS, respectively. The average cost of sending a datum by a sentinel site per week was higher for the forms (5.0 USD) than for the EWS (0.9 USD) and SMS (0.1 USD). The number of outpatient visits and subsequently all surveillance data decreased across the years 2017‐2019 together with the influenza positivity rate from 30.7% to 28.3%. Contrarily, the proportion of influenza‐associated ILI to outpatient load was highest in the year 2019 (0.37 per 100 persons vs 0.28 and 0.26 in the other 2 years).

Conclusion

All sentinel sites and even other disease surveillance systems are expected to use this tool in the near term future due to its satisfactory performance and cost.