Corrigendum: Decreased influenza activity during the COVID-19 pandemic in Ghana, 2020.

[This corrects the article DOI: 10.3389/fpubh.2023.1290553.].

Yellow fever in Ghana: Predicting emergence and ecology from historical outbreaks.

Understanding the epidemiology and ecology of yellow fever in endemic regions is critical for preventing future outbreaks. Ghana is a high-risk country for yellow fever. In this study we estimate the epidemiology, ecological cycles, and areas at risk for yellow fever in Ghana based on historical outbreaks. We identify 2371 cases and 887 deaths (case fatality rate 37.4%) from yellow fever reported in Ghana from 1910 to 2022. Since implementation of routine childhood vaccination in 1992, the estimated mean annual number of cases decreased by 81% and the geographic distribution of yellow fever cases also changed. While there have been multiple large historical outbreaks of yellow fever in Ghana from the urban cycle, recent outbreaks have originated among unvaccinated nomadic groups in rural areas with the sylvatic/savanna cycles. Using machine learning and an ecological niche modeling framework, we predict areas in Ghana that are similar to where prior yellow fever outbreaks have originated based on temperature, precipitation, landcover, elevation, and human population density. We find differences in predictions depending on the ecological cycles of outbreaks. Ultimately, these findings and methods could be used to inform further subnational risk assessments for yellow fever in Ghana and other high-risk countries.

The role of digital surveillance during outbreaks: the Ghana experience from COVID-19 response.

Over the years, Ghana has made notable strides in adopting digital approaches to address societal challenges and meet demands. While the health sector, particularly the disease surveillance structure, has embraced digitization to enhance case detection, reporting, analysis, and information dissemination, critical aspects remain to be addressed. Although the Integrated Disease Surveillance and Response (IDSR) structure has experienced remarkable growth in digitization, certain areas require further attention as was observed during the COVID-19 pandemic. Ghana during the COVID-19 pandemic, recognized the importance of leveraging digital technologies to bolster the public health response. To this end, Ghana implemented various digital surveillance tools to combat the pandemic. These included the 'Surveillance Outbreak Response Management and Analysis System (SORMAS)', the digitalized health declaration form, ArcGIS Survey123, Talkwalker, 'Lightwave Health information Management System' (LHIMS), and the 'District Health Information Management System (DHIMS)'. These digital systems significantly contributed to the country's success in responding to the COVID-19 pandemic. One key area where digital systems have proved invaluable is in the timely production of daily COVID-19 situational updates. This task would have been arduous and delayed if reliant solely on paper-based forms, which hinder efficient reporting to other levels within the health system. By adopting these digital systems, Ghana has been able to overcome such challenges and provide up-to-date information for making informed public health decisions. This paper attempts to provide an extensive description of the digital systems currently employed to enhance Ghana's paper-based disease surveillance system in the context of its response to COVID-19. The article explores the strengths and challenges or limitations associated with these digital systems for responding to outbreaks, offering valuable lessons that can be learned from their implementation.

Facilitators and Barriers in the Implementation of a Digital Surveillance and Outbreak Response System in Ghana Before and During the COVID-19 Pandemic: Qualitative Analysis of Stakeholder Interviews.

BACKGROUND: In the past 2 decades, many countries have recognized the use of electronic systems for disease surveillance and outbreak response as an important strategy for disease control and prevention. In low- and middle-income countries, the adoption of these electronic systems remains a priority and has attracted the support of global health players. However, the successful implementation and institutionalization of electronic systems in low- and middle-income countries have been challenged by the local capacity to absorb technologies, decisiveness and strength of leadership, implementation costs, workforce attitudes toward innovation, and organizational factors. In November 2019, Ghana piloted the Surveillance Outbreak Response Management and Analysis System (SORMAS) for routine surveillance and subsequently used it for the national COVID-19 response. OBJECTIVE: This study aims to identify the facilitators of and barriers to the sustainable implementation and operation of SORMAS in Ghana. METHODS: Between November 2021 and March 2022, we conducted a qualitative study among 22 resource persons representing different stakeholders involved in the implementation of SORMAS in Ghana. We interviewed study participants via telephone using in-depth interview guides developed consistent with the model of diffusion of innovations in health service organizations. We transcribed the interviews verbatim and performed independent validation of transcripts and pseudonymization. We performed deductive coding using 7 a priori categories: innovation, adopting health system, adoption and assimilation, diffusion and dissemination, outer context, institutionalization, and linkages among the aspects of implementation. We used MAXQDA Analytics Pro for transcription, coding, and analysis. RESULTS: The facilitators of SORMAS implementation included its coherent design consistent with the Integrated Disease Surveillance and Response system, adaptability to evolving local needs, relative advantages for task performance (eg, real-time reporting, generation of case-base data, improved data quality, mobile offline capability, and integration of laboratory procedures), intrinsic motivation of users, and a smartphone-savvy workforce. Other facilitators were its alignment with health system goals, dedicated national leadership, political endorsement, availability of in-country IT capacities, and financial and technical support from inventors and international development partners. The main barriers were unstable technical interoperability between SORMAS and existing health information systems, reliance on a private IT company for data hosting, unreliable internet connectivity, unstable national power supply, inadequate numbers and poor quality of data collection devices, and substantial dependence on external funding. CONCLUSIONS: The facilitators of and barriers to SORMAS implementation are multiple and interdependent. Important success conditions for implementation include enhanced scope and efficiency of task performance, strong technical and political stewardship, and a self-motivated workforce. Inadequate funding, limited IT infrastructure, and lack of software development expertise are mutually reinforcing barriers to implementation and progress to country ownership. Some barriers are external, relate to the overall national infrastructural development, and are not amenable even to unlimited project funding.

Call detail record aggregation methodology impacts infectious disease models informed by human mobility.

This paper demonstrates how two different methods used to calculate population-level mobility from Call Detail Records (CDR) produce varying predictions of the spread of epidemics informed by these data. Our findings are based on one CDR dataset describing inter-district movement in Ghana in 2021, produced using two different aggregation methodologies. One methodology, "all pairs," is designed to retain long distance network connections while the other, "sequential" methodology is designed to accurately reflect the volume of travel between locations. We show how the choice of methodology feeds through models of human mobility to the predictions of a metapopulation SEIR model of disease transmission. We also show that this impact varies depending on the location of pathogen introduction and the transmissibility of infections. For central locations or highly transmissible diseases, we do not observe significant differences between aggregation methodologies on the predicted spread of disease. For less transmissible diseases or those introduced into remote locations, we find that the choice of aggregation methodology influences the speed of spatial spread as well as the size of the peak number of infections in individual districts. Our findings can help researchers and users of epidemiological models to understand how methodological choices at the level of model inputs may influence the results of models of infectious disease transmission, as well as the circumstances in which these choices do not alter model predictions.

Molecular Characterization of Circulating Yellow Fever Viruses from Outbreak in Ghana, 2021-2022.

Yellow fever virus, transmitted by infected Aedes spp. mosquitoes, causes an acute viral hemorrhagic disease. During October 2021-February 2022, a yellow fever outbreak in some communities in Ghana resulted in 70 confirmed cases with 35 deaths (case-fatality rate 50%). The outbreak started in a predominantly unvaccinated nomadic community in the Savannah region, from which 65% of the cases came. The molecular amplification methods we used for diagnosis produced full-length DNA sequences from 3 confirmed cases. Phylogenetic analysis characterized the 3 sequences within West Africa genotype II; strains shared a close homology with sequences from Cote d'Ivoire and Senegal. We deployed more sensitive advanced molecular diagnostic techniques, which enabled earlier detection, helped control spread, and improved case management. We urge increased efforts from health authorities to vaccinate vulnerable groups in difficult-to-access areas and to educate the population about potential risks for yellow fever infections.

Risk factors for COVID-19 infections among health care workers in Ghana.

INTRODUCTION: Health care workers (HCWs) are crucial to the fight against COVID-19 and are at risk of being infected. We sought to determine the risk factors and associations of COVID-19 among HCWs in Ghana during the period of the pandemic. MATERIALS AND METHODS: A case-control study was conducted using the WHO COVID-19 HCWs exposure risk assessment tool. A HCW was categorized as "high risk" for COVID-19 if s/he did not respond "always, as recommended" to adherence to Infection Prevention and Control (IPC) measures during a healthcare interaction. A HCW was categorized as "low risk" if s/he responded "always, as recommended" to adherence to IPC measures. We used univariate and multiple logistic regression models to determine associated risk factors. Statistical significance was set at 5%. RESULTS: A total of 2402 HCWs were recruited and the mean age was 33.2±7.1 years. Almost 87% (1525/1745) of HCWs had high risk for COVID-19 infection. Risk factors identified were profession (doctor- aOR: 2.13, 95%CI: 1.54-2.94; radiographer-aOR: 1.16, 95% CI: 0.44-3.09)), presence of comorbidity (aOR: 1.89, 95%CI: 1.29-2.78), community exposure to virus (aOR: 1.26, 95% CI: 1.03-1.55), not performing hand hygiene before and after aseptic procedures performed (aOR: 1.6, 95% CI: 1.05-2.45); not frequently decontaminating high-touch surfaces always as recommended (aOR: 2.31, 95%CI: 1.65-3.22; p = 0.001) and contact with a confirmed COVID-19 patient (aOR: 1.39, 95% CI: 1.15-1.67). Among those who came into any form of contact with confirmed COVID-19 patient, providing direct care (aOR: 2.0, 95%CI: 1.36-2.94), face-to-face contact (aOR: 2.23, 95%CI: 1.41-3.51), contact with environment/materials used by COVID-19 patient (aOR: 2.25, 95%CI: 1.45-3.49) and presence during conduct of aerosol generating procedures (aOR: 2.73, 95%CI: 1.74-4.28) were associated with COVID-19 infection. CONCLUSION: Non-adherence to IPC guidelines puts HCWs at increased risk of COVID-19 infection thus ensuring IPC adherence is key to reducing this risk.

Repurposing an integrated national influenza platform for genomic surveillance of SARS-CoV-2 in Ghana: a molecular epidemiological analysis.

BACKGROUND: Genomic surveillance of SARS-CoV-2 is crucial for monitoring the spread of COVID-19 and guiding public health decisions, but the capacity for SARS-CoV-2 testing and sequencing in Africa is low. We integrated SARS-CoV-2 surveillance into an existing influenza surveillance network with the aim of providing insights into SARS-CoV-2 transmission and genomics in Ghana. METHODS: In this molecular epidemiological analysis, which is part of a wider multifaceted prospective observational study, we collected national SARS-CoV-2 test data from 35 sites across 16 regions in Ghana from Sept 1, 2020, to Nov 30, 2021, via the Ghanaian integrated influenza and SARS-CoV-2 surveillance network. SARS-CoV-2-positive samples collected through this integrated national influenza surveillance network and from international travellers arriving in Accra were sequenced with Oxford Nanopore Technology sequencing and the ARTIC tiled amplicon method. The sequence lineages were typed with pangolin and the phylogenetic analysis was conducted with IQ-Tree2 and TreeTime. FINDINGS: During the study period, 5495 samples were submitted for diagnostic testing through the national influenza surveillance network (2121 [46·1%] of 4021 samples with complete demographic data were from female individuals and 2479 [53·9%] of 4021 samples were from male individuals). We also obtained 2289 samples from travellers who arrived in Accra and had a positive lateral flow test, of whom 1626 (71·0%, 95% CI 69·1-72·9) were confirmed to be SARS-CoV-2 positive. Co-circulation of influenza and SARS-CoV-2 in Ghana was detected, with increased cases of influenza in November, 2020, November, 2021, and January and June, 2021. In 4124 samples from individuals with influenza-like illness, SARS-CoV-2 was identified in 583 (14·1%, 95% CI 13·1-15·2) samples and influenza in 356 (8·6%, 7·8-9·5). Conversely, in 476 samples from individuals with of severe acute respiratory illness, SARS-CoV-2 was detected in 58 (12·2%, 9·5-15·5) samples and influenza in 95 (19·9%, 16·5-23·9). We detected four waves of SARS-CoV-2 infections in Ghana; each wave was driven by a different variant: B.1 and B.1.1 were the most prevalent lineages in wave 1, alpha (B.1.1.7) was responsible for wave 2, delta (B.1.617.2) and its sublineages (closely related to delta genomes from India) were responsible for wave 3, and omicron variants were responsible for wave 4. We detected omicron variants among 47 (32%) of 145 samples from travellers during the start of the omicron spread in Ghana (wave 4). INTERPRETATION: This study shows the value of repurposing existing influenza surveillance platforms to monitor SARS-CoV-2. Influenza continued to circulate in Ghana in 2020 and 2021, and remained a major cause of severe acute respiratory illness. We detected importations of SARS-CoV-2 variants into Ghana, including those that did or did not lead to onward community transmission. Investment in strengthening national influenza surveillance platforms in low-income and middle-income countries has potential for ongoing monitoring of SARS-CoV-2 and future pandemics. FUNDING: The EDCTP2 programme supported by the EU.

Leaving no disease behind: The roadmap to securing universal health security and what this means for the surveillance of infectious diseases in Ghana as a precedent for sub-Saharan Africa.

INTRODUCTION: Ghana is the first country in sub-Saharan Africa (SSA) to aim for universal health coverage (UHC). Based on Ghana's UHC system, the accessibility and distribution of healthcare facilities were evaluated for 2020. Projecting into 2030, this study aimed at providing geographical information data for guiding future policies on siting required healthcare facilities. Ghana as a precedent for SSA was evaluated and proposed to "leave no disease behind" in the surveillance of infectious diseases (IDs). This is to reinforce the sustainable development goals (SDG) 3 agenda on health that underpins monitoring equity in "leaving no one behind." METHODS: Geospatial accessibility, travel time data, and algorithms were employed to evaluate the universality and accessibility of healthcare facilities, and their future projections to meet UHC by 2030. Healthcare facilities as surveillance sites were compared to community-based surveillance to identify which would be more applicable as a surveillance system to leave no disease behind in Ghana. FINDINGS: Ghana has 93.8%, 6.1% and 0.1% as primary, secondary and tertiary healthcare facilities respectively. It has 26.1% of healthcare facilities remaining to meet the SDG 3 health target by 2030. In terms of providing quality healthcare, 29.3% and 67.2% of the additional required healthcare facilities for optimal allocation and achieving the UHC target need to be secondary and tertiary respectively. In assessing the broad spectrum of IDs studied from 2000 to 2020, an average of 226 IDs were endemic or potentially endemic to Ghana. The majority of the studies carried out to identify these IDs were done through community-based surveillance. CONCLUSION: Establishing community-based surveillance sites to leave no disease behind and also providing the required healthcare facilities to reinforce leaving no one behind will enhance the universal health security of Ghana as a precedent for SSA.

An assessment of the laboratory network in Ghana: A national-level ATLAS survey (2019-2020).

Background: Integrated health systems with strong laboratory networks are critical in improving public health. The current study assessed the laboratory network in Ghana and its functionality using the Assessment Tool for Laboratory Services (ATLAS). Intervention: A national-level laboratory network survey was conducted among stakeholders of the Ghanaian laboratory network in Accra. Face-to-face interviews were conducted from December 2019 to January 2020, with follow-up phone interviews between June and July 2020. Also, we reviewed supporting documents provided by stakeholders for supplementary information and transcribed these to identify themes. Where possible, we completed the Laboratory Network scorecard using data obtained from the ATLAS. Lessons learnt: The Laboratory Network (LABNET) scorecard assessment was a valuable addition to the ATLAS survey as it quantified the functionality of the laboratory network and its overall advancement toward achieving International Health Regulations (2005) and Global Health Security Agenda targets. Two significant challenges indicated by respondents were laboratory financing and delayed implementation of the Ghana National Health Laboratory Policy. Recommendations: Stakeholders recommended a review of the country's funding landscape, such as funding laboratory services from the country's internally generated funds. Also, they recommended laboratory policy implementation to ensure adequate laboratory workforce and standards.

Post introduction evaluation of the malaria vaccine implementation programme in Ghana, 2021.

BACKGROUND: Malaria remains a public health challenge in Sub-Saharan Africa with the region contributing to more than 90% of global cases in 2020. In Ghana, the malaria vaccine was piloted to assess the feasibility, safety, and its impact in the context of routine use alongside the existing recommended malaria control measures. To obtain context-specific evidence that could inform future strategies of introducing new vaccines, a standardized post-introduction evaluation (PIE) of the successes and challenges of the malaria vaccine implementation programme (MVIP) was conducted. METHODS: From September to December 2021, the WHO Post-Introduction Evaluation (PIE) tool was used to conduct a mixed methods evaluation of the MVIP in Ghana. To ensure representativeness, study sites and participants from the national level, 18 vaccinating districts, and 54 facilities from six of the seven pilot regions were purposively selected. Quantitative and qualitative data were collected using data collection tools that were adapted based on the WHO PIE protocol. We performed summary descriptive statistics on quantitative data, thematic analysis on qualitative data, and triangulation of the results from both sets of analyses. RESULTS: About 90.7% (49/54) of health workers stated that the vaccine introduction process was smooth and contributed to an overall improvement of routine immunisation services. About 87.5% (47/54) of healthcare workers, and 95.8% (90/94) of caregivers accepted RTS,S malaria vaccine. Less than half [46.3%; (25/54)] of the healthcare workers participated in the pre-vaccine introduction training but almost all [94.4%; (51/54)] were able to constitute and administer the vaccine appropriately. About 92.5% (87/94) of caregivers were aware of the RTS,S introduction but only 44.0% (44/94) knew the number of doses needed for maximum protection. Health workers believed that the MVIP has had a positive impact on under five malaria morbidity. CONCLUSIONS: The malaria vaccine has been piloted successfully in Ghana. Intensive advocacy; community engagement, and social mobilization; and regular onsite supportive supervision are critical enablers for successful introduction of new vaccines. Stakeholders are convinced of the feasibility of a nationwide scale up using a phased subnational approach taking into consideration malaria epidemiology and global availability of vaccines.

SARS-CoV-2 Molecular Evolutionary Dynamics in the Greater Accra Region, Ghana.

To assess dynamics of SARS-CoV-2 in Greater Accra Region, Ghana, we analyzed SARS-CoV-2 genomic sequences from persons in the community and returning from international travel. The Accra Metropolitan District was a major origin of virus spread to other districts and should be a primary focus for interventions against future infectious disease outbreaks.

Response to back-to-back outbreaks of circulating vaccine-derived poliovirus type 2 in two nomadic pastoralist settlements in Oti Region, Ghana-2019.

BACKGROUND: The global switch from trivalent oral poliovirus vaccine (OPV) to bivalent OPV in April 2016 without corresponding co-administration of inactivated poliovirus vaccine (IPV) until June 2018, created a cohort of poliovirus type 2 naïve children with risk of developing vaccine-derived poliovirus type 2 (VDPV2). In November and December 2019, two cases of circulating vaccine-derived poliovirus type 2 (cVDPV2) were confirmed in quick succession through Acute Flaccid Paralysis (AFP) surveillance in two nomadic pastoralist settlements in Oti Region. We investigated to determine the outbreak extent, identify risk factors and implement control and preventive measures. METHODS: We interviewed case-patients' families, abstracted immunization records, assessed AFP surveillance and conducted rapid OPV and IPV vaccination coverage surveys. Using AFP case definition of any child less than 15 years in the community with sudden onset of paralysis from July to November 2019 (in case-patient 1's district) and August to December 2019 (in case-patient 2's district), we conducted active case search. Stool samples from apparently healthy children and close contacts of the case-patients were collected and tested for poliovirus. We conducted environmental assessment of the community to identify potential risk factors. RESULTS: Case-patient 1 was an eight-year-old female who had taken two doses of OPV while case-patient 2 was an eight-month-old male who had taken three out of required four OPV doses in addition to IPV at seven months. Families of both case-patients had either travelled to or received visitors from areas with confirmed cVDPV2. Of all children surveyed, eight (29.6%) of 27 and three (18.8%) of 16 eligible children in communities of case-patient 1 and 2 respectively had received required four doses of OPV. No AFP case was found in both communities and surrounding settlements. Both communities had no source of potable water and toilet facilities. A stool sample from a contact of case-patient 1 tested positive for cVDPV2. CONCLUSION: Outbreaks of cVDPV2 occurred in insanitary, under-vaccinated nomadic pastoralist settlements in Oti Region. Three rounds of monovalent OPV vaccination campaigns for children under 5 years of age in the districts and region as well as countrywide IPV vaccination campaign for poliovirus type 2 naïve cohort were conducted.

Decreased influenza activity during the COVID-19 pandemic in Ghana, 2020.

Introduction: The COVID-19 pandemic had a significant effect on influenza activity globally. In this study, we analyzed trends of influenza activity in 2020 during the COVID-19 pandemic in Ghana. Methods: This was a cross-sectional study using active prospective influenza surveillance data from 29 sentinel sites. At the sentinel sites, we enrolled patients presenting with symptoms based on the WHO case definition for influenza-like illness (ILI) and severe acute respiratory illness (SARI). Oro and nasopharyngeal swabs were collected from patients and tested for the presence of influenza viruses using specific primers and probes described by the US-CDC. The percentage of positivity for influenza between 2017-2019 and 2021 was compared to 2020. Using the test for proportions in STATA 17.0 we estimated the difference in influenza activities between two periods. Results and discussion: Influenza activity occurred in a single wave during the 2020 surveillance season into 2021, September 28 2020-March 7 2021 (week 40, 2020-week 9, 2021). Influenza activity in 2020 was significantly lower compared to previous years (2017- 2019, 2021). Influenza A (H3) was more commonly detected during the early part of the year (December 30, 2019-March 8, 2020), while influenza B Victoria was more commonly detected toward the end of the year (September 28-December 28). In Ghana, adherence to the community mitigation strategies introduced to reduce transmission of SARS-CoV-2, which affected the transmission of other infectious diseases, may have also impacted the transmission of influenza. To the best of our knowledge, this is the first study in Ghana to describe the effect of the COVID-19 pandemic on influenza activity. The continuation and strict adherence to the non-pharmaceutical interventions at the community level can help reduce influenza transmission in subsequent seasons.

Using drones to transport suspected COVID-19 samples; experiences from the second largest testing centre in Ghana, West Africa.

BACKGROUND: The declaration of COVID-19 as a pandemic on March 11 2020, by the World Health Organisation prompted the need for a sustained and a rapid international response. In a swift response, the Government of Ghana, in partnership with Zipline company, launched the use of Unmanned Automated Vehicles (UAV) to transport suspected samples from selected districts to two foremost testing centres in the country. Here, we present the experiences of employing this technology and its impact on the transport time to the second largest testing centre, the Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR) in Kumasi, Ghana. METHODS: Swab samples collected from suspected COVID-19 patients were transported to the Zipline office by health workers. Information on the samples were sent to laboratory personnel located at KCCR through a WhatsApp platform to get them ready to receive the suspected COVID-19 samples while Zipline repackaged samples and transported them via drone. Time of take-off was reported as well as time of drop-off. RESULTS: A total of 2537 COVID-19 suspected samples were received via drone transport from 10 districts between April 2020 to June 2021 in 440 deliveries. Ejura-Sekyedumase District Health Directorate delivered the highest number of samples (765; 30%). The farthest district to use the drone was Pru East, located 270 km away from KCCR in Kumasi and 173 km to the Zipline office in Mampong. Here, significantly, it took on the average 39 minutes for drones to deliver samples compared to 117 minutes spent in transporting samples by road (p<0.001). CONCLUSION: The use of drones for sample transport during the COVID-19 pandemic significantly reduced the travel time taken for samples to be transported by road to the testing site. This has enhanced innovative measures to fight the pandemic using technology.

Diarrhea-Causing Bacteria and Their Antibiotic Resistance Patterns Among Diarrhea Patients From Ghana.

Diarrheal disease remains a major global health problem particularly in children under 5 years and the emergence of antibiotic-resistant strains of causative pathogens could slow control efforts, particularly in settings where treatment options are limited. This surveillance study conducted in Ghana aimed to determine the prevalence and antimicrobial susceptibility profile of diarrhea-causing bacteria. This was a cross-sectional study carried out in five health facilities in the Ga West Municipality of Ghana between 2017 and 2021. Diarrheic stool samples from patients were collected and cultured on standard differential/selective media and isolates identified by standard biochemical tests, MALDI-TOF assay, and serological analysis. The antibiogram was determined using Kirby-Bauer disk diffusion and Microscan autoScan4 MIC panels which were used for extended-spectrum beta-lactamase (ESBL) detection. Bacteria were isolated from 97.5% (772/792) of stool samples, and 167 of the isolates were diarrheagenic and met our inclusion criteria for antimicrobial resistance (AMR) analysis. These included Escherichia coli (49.1%, 82/167), Salmonella species (23.9%, 40/167), Vibrio species (16.8%, 28/167), and Shigella species (10.2%, 17/167). Among 24 Vibrio species, we observed resistances to cefotaxime (21/24, 87.5%), ceftriaxone (20/24, 83.3%), and ciprofloxacin (6/24, 25%), including four multi-drug resistant isolates. All 13 Vibrio parahaemolyticus isolates were resistant to cefazolin. All 17 Shigella isolates were resistant to tetracycline with resistance to shigellosis drugs such as norfloxacin and ciprofloxacin. Salmonella isolates were highly susceptible to norfloxacin (40/40, 100%) and tetracycline (12/34, 35%). Two ESBL-producing E. coli were also identified with marked susceptibility to gentamicin (66/72, 91.7%) and amikacin (57/72, 79.2%) prescribed in the treatment of E. coli infections. This study showed the different bacteria implicated in diarrhea cases in Ghana and the need for differential diagnoses for better treatment outcomes. Escherichia coli, Shigella, Salmonella, and Vibrio have all been implicated in diarrhea cases in Ghana. The highest prevalence was E. coli and Salmonella with Shigella the least prevalent. Resistance to commonly used drugs found in these isolates may render bacteria infection treatment in the near future nearly impossible. Routine antimicrobial susceptibility testing, effective monitoring, and nationwide surveillance of AMR pathogens should be implemented to curb the increase of antimicrobial resistance in Ghana.

An evaluation of the diagnostic performance characteristics of the Yellow Fever IgM immunochromatographic rapid diagnostic test kit from SD Biosensor in Ghana.

Yellow fever is endemic in Ghana and outbreaks occur periodically. The prodromal signs due to Yellow Fever Virus (YFV) infection are non-specific, making clinical signs unreliable as the sole criteria for diagnosis. Accurate laboratory confirmation of suspected yellow fever cases is therefore vital in surveillance programs. Reporting of ELISA IgM testing results by laboratories can delay due to late arrival of samples from the collection sites as well as limited availability of ELISA kits. In this study, the diagnostic performance characteristics of a rapid immunochromatographic Standard Q Yellow Fever IgM test kit (SD Biosensor) was evaluated for the rapid diagnosis of Yellow Fever infection in Ghana. A panel of 275 sera, comprising 81 confirmed YFV positives and 194 negatives were re-tested in this study using the Standard Q Yellow Fever IgM test kit. Using the CDC/WHO Yellow Fever IgM capture ELISA as a benchmark, the sensitivity, specificity and accuracy of the Standard Q Yellow Fever test kit were 96.3%, 97.9% and 97.5%, respectively. The false positivity rate was 5.1% and there was no cross-reactivity when the Standard Q Yellow Fever test kit was tested against dengue, malaria and hepatitis B and C positive samples. In addition, inter-reader variability and invalid rate were both zero. The results indicate that the diagnostic performance of the Standard Q Yellow Fever IgM test kit on serum or plasma is comparable to the serum IgM detection by ELISA and can be used as a point of care rapid diagnostic test kit for YFV infection in endemic areas.

Association between mobility, non-pharmaceutical interventions, and COVID-19 transmission in Ghana: A modelling study using mobile phone data.

Governments around the world have implemented non-pharmaceutical interventions to limit the transmission of COVID-19. Here we assess if increasing NPI stringency was associated with a reduction in COVID-19 cases in Ghana. While lockdowns and physical distancing have proven effective for reducing COVID-19 transmission, there is still limited understanding of how NPI measures are reflected in indicators of human mobility. Further, there is a lack of understanding about how findings from high-income settings correspond to low and middle-income contexts. In this study, we assess the relationship between indicators of human mobility, NPIs, and estimates of Rt, a real-time measure of the intensity of COVID-19 transmission. We construct a multilevel generalised linear mixed model, combining local disease surveillance data from subnational districts of Ghana with the timing of NPIs and indicators of human mobility from Google and Vodafone Ghana. We observe a relationship between reductions in human mobility and decreases in Rt during the early stages of the COVID-19 epidemic in Ghana. We find that the strength of this relationship varies through time, decreasing after the most stringent period of interventions in the early epidemic. Our findings demonstrate how the association of NPI and mobility indicators with COVID-19 transmission may vary through time. Further, we demonstrate the utility of combining local disease surveillance data with large scale human mobility data to augment existing surveillance capacity to monitor the impact of NPI policies.