Five years of malaria control in the continental region, Equatorial Guinea

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Study Justification:
The study aimed to evaluate the impact of a malaria control program in Equatorial Guinea. The program, which began in 2004 on Bioko Island, was expanded to the four mainland provinces of Equatorial Guinea in 2007. The study aimed to assess the coverage and effectiveness of interventions, such as long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS), in reducing malaria transmission.
Highlights:
– The study found that the proportion of children aged 1-4 using LLINs or living in a sprayed house increased from 23% in 2007 to 42% in 2011.
– The prevalence of Plasmodium falciparum infection in children aged 1-4 decreased from 68% in 2007 to 52% in 2011.
– Children who used LLINs or lived in a sprayed house had lower prevalence of infection compared to those with no intervention.
– Children who both used LLINs and lived in a sprayed house had the lowest prevalence of infection.
– High site-level intervention coverage did not always correlate with lower site-level P. falciparum prevalence.
– The malaria season peaked in either June or July, not necessarily coinciding with data collection.
Recommendations:
– Increase the scale-up coverage of LLINs and IRS to further reduce malaria transmission.
– Emphasize the importance of using both LLINs and IRS for maximum protection against malaria.
– Improve coordination and implementation of interventions to ensure high coverage and effectiveness.
– Consider adjusting intervention timing to align with the peak malaria season.
Key Role Players:
– Ministry of Health and Social Welfare of Equatorial Guinea
– Local health facilities and health workers
– Non-governmental organizations (NGOs) involved in malaria control
– Community leaders and volunteers
Cost Items:
– Procurement and distribution of LLINs
– Procurement and implementation of IRS
– Training for health workers on case management and intervention implementation
– Information, education, and communication campaigns
– Monitoring and evaluation activities
– Data collection and analysis
Please note that the cost items provided are general categories and not actual cost figures.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study provides estimates of intervention coverage and indicators of malaria transmission over a five-year period. It also includes data from annual malaria indicator surveys, health information systems, and entomological monitoring. The study uses logistic regression to estimate the personal protection offered by long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) against Plasmodium falciparum infection. However, the abstract does not provide information on the sample size, methodology, or statistical significance of the findings. To improve the strength of the evidence, the abstract should include these details and provide more context on the limitations of the study.

Background: A successful malaria control programme began in 2004 on Bioko Island, Equatorial Guinea. From 2007, the same multiple malaria interventions, though reduced in scope for funding reasons, were introduced to the four mainland provinces of Equatorial Guinea (the continental region) aiming to recreate Bioko’s success. Two provinces received long-lasting insecticidal nets (LLINs) and two provinces received biannual indoor residual spraying (IRS). Enhanced case management and communications were introduced throughout. Methods. Estimates of intervention coverage and indicators of malaria transmission for 2007 to 2011 were derived from annual malaria indicator surveys (MIS). Results were complemented by health information system (HIS) and entomological data. The personal protection offered by LLINs and IRS against Plasmodium falciparum infection was estimated with logistic regression. Results: The estimated proportion of children aged 1-4 using either an LLIN the previous night or living in a house sprayed in the last six months was 23% in 2007 and 42% in 2011. The estimated prevalence of P. falciparum in children aged 1-4 was 68% (N=1,770; 95% confidence interval [CI]: 58-76%) in 2007 and 52% (N=1,602; 95% CI: 44-61%) in 2011. Children 1-4 years had lower prevalence if they used an LLIN the previous night (N=1,124, 56%; adjusted odds ratio [aOR] 0.64, 95% CI: 0.55-0.74) or if they lived in a sprayed house (N=1,150, 57%; aOR 0.80, 95% CI: 0.62-1.03) compared to children with neither intervention (N=4,131, 66%, reference group). The minority of children who both used an LLIN and lived in a sprayed house had the lowest prevalence of infection (N=171, 45%; aOR 0.52, 95% CI: 0.35-0.78). High site-level intervention coverage did not always correlate with lower site-level P. falciparum prevalence. The malaria season peaked in either June or July, not necessarily coinciding with MIS data collection. Conclusions: Though moderate impact was achieved after five years of vector control, case management, and communications, prevalence remained high due to an inability to sufficiently scale-up coverage with either IRS or LLINs. Both LLINs and IRS provided individual protection, but greater protection was afforded to children who benefitted from both. © 2013 Rehman et al.; licensee BioMed Central Ltd.

Equatorial Guinea is located on the West Coast of Central Africa at approximately 3° N latitude and 9° E longitude. It is bordered by Cameroon to the North and Gabon to the West and South. The country consists of seven provinces, four of which form the mainland or continental region, the location of the EGMCI. The continental region measures approximately 26,000 km2 in area. In 2011, its population was estimated to be almost one million (unpublished data, BIMCP; based on a 2.9% per annum increase from the 2001 population census estimate of three-quarters of a million). Equatorial Guinea has large off-shore oil reserves that began to be exploited extensively in 1997 resulting in a gross national income per capita of more than US$20,000 in 2011 [4] meaning the World Bank classify Equatorial Guinea as a high income country. Adult literacy is high (93% in 2011). In spite of extensive investments within the country in recent years, it remains under-developed with wealth unevenly distributed, and life expectancy at birth estimated to be 51 years. Equatorial Guinea was ranked 136 on the United Nations Human Development Index in 2011 [4]. The nation has had two rulers since gaining independence from Spain in 1968. The majority of people are of Fang ethnicity (of Bantu origin) and are Roman Catholic. The wet seasons in the continental region runs from February to June and from September to December. Rainfall is highest on the coast, averaging 2,300 mm per annum in Bata whilst inland, in Mico Miseng, it is 1,500 mm. Temperature averages 26°C and the humidity is high year round. Malaria in the continental region is stable and hyper-endemic [5,6]. Transmission occurs year round at much higher levels than on the island of Bioko. The primary malaria vector is Anopheles gambiae sensu lato (s.l.), although three other species are also involved in transmission [7,8]. The use of LLINs and IRS was low before the EGMCI started [9]. The multiple malaria interventions that made up the EGMCI included both prevention through vector control and treatment through improved case management (Figure 1) as well as a comprehensive and integrated communications strategy designed to enhance knowledge, change behaviours and improve control-related practices. Timing of malaria interventions, Equatorial Guinea 2007 to 2011. A malaria indicator survey (MIS- blue solid lines) was carried out prior to implementation of any interventions in 2007 and then annually. Subsequently two provinces received interventions in 2007. Indoor residual spraying (IRS- lines with a long dash and two dots) commenced in Litoral (L, the coastal province) and long lasting insecticide treated bed nets (LLINs- dashed lines) were distributed in Centro Sur (CS, the province immediately east of Litoral). After the second MIS Artemisin combination therapy (Artesunate 50 mg + Amodiqaquine Hydrochloride 200 mg: denoted as ACT- green lines) was introduced region-wide and the remaining two provinces commenced vector control. Kie-Ntem (KN, the province in the far north east of the region) received IRS and Wele-Nzas (WN, the province in the south east of the region) received LLINs. Pregnant women attending ante-natal clinics region-wide received LLINs from 2009. Intervention activity stopped in August 2011. Information, education and communication campaigns ran throughout the intervention period as described in the text. Training for laboratory staff was carried out from 2009 until June 2011. *In water locked communities where IRS was not feasible. PermaNet 2.0 (Vestergaard Frandsen) LLINs were distributed free-of-charge in Centro Sur Province from June through August 2007 and subsequently in Wele-Nzas Province from August through October 2008. A total of 146,608 nets were distributed. Quality control that was undertaken immediately after each of the LLIN mass distribution campaigns using Lot Quality Assurance Sampling (LQAS) [10] to identify lots where less than 90% of the houses had been visited by Red Cross volunteers, where less than 80% of the sleeping areas had received a net, and/or where less than 50% of the distributed nets were hung. Any lot failing either of these coverage targets were visited by a mop-up team. In addition to supply coverage, the LQAS surveys were used to evaluate usage rates among children less than five years of age. These surveys indicated that high supply coverage rates were rapidly achieved and usage rates increased to moderately high levels. For example, LQAS during LLIN distribution in Centro Sur in 2007 revealed that 66% children had slept under an LLIN the previous night. Similarly, in Wele Nsas the LQAS revealed that 60% of the children had slept under an LLIN the previous night. LLINs were later distributed in 40 villages in southern Litoral province (Kogo and Mbini sites) which had initially received IRS. These 40 villages were inaccessible for the annual MIS. Pregnant women attending antenatal clinics in all four provinces also received LLINs from 2009 through 2011. A first round of indoor residual spraying was commenced in Litoral Province in June 2007 and was completed in December 2007. From March 2008 through September 2008, a second round of IRS was conducted in Litoral Province and a first round was conducted in Kie Ntem Province. From 2009 through 2011, due to a reorganization of the spray plan, two rounds of IRS were conducted in each province, the first occurring from February through March, and the second from August through September. A rotational insecticide scheme was used starting initially with four rounds of the pyrethoid insecticide Alpha Cypermethrin (Fendona™, Avima/BASF, South Africa and HI Kara, India), followed by one round of the carbamate insecticide bendiocarb (Ficam™, Bayer, South Africa), and ending with three rounds of the pyrethroid insecticide deltamethrin (K-Orthrin™, Bayer, South Africa) (Figure 1). All four provinces were targeted for improvements to case management. Artemisinin-based combination therapy (ACT) was provided free-of-charge for uncomplicated malaria from June 2008 until August 2011 with Artesunate 50 mg + Amodiaquine Hydrochloride 200 mg (IDA foundation, The Netherlands; Arsuamoon™, Ghillin Pharmaceuticals Co.Ltd., China; Larimal™, IPCA Laboratories, India; and Coarsucum™, Sanofi Aventis, France). Patients suffering from severe malaria were also treated free-of-charge in accordance with the national treatment guidelines using injectable Artemether (Dafra Pharma GMBH, Switzerland). Diagnostic capacity was also improved. Rapid diagnostic tests (RDT; ICT™ Malaria P.f. Cassette ML01, R&R, Cape Town, South Africa) were distributed to health centres and health posts not equipped with a laboratory. In health centres with laboratories, and all hospitals, malaria diagnosis was confirmed by blood slide. Over the five-year duration of the project, 3,774 training sessions were conducted for individual service providers to improve and reinforce their diagnosis and treatment of uncomplicated and severe malaria. Malaria prevention was promoted through comprehensive information, education and communication (IEC) messaging delivered through mass media, group-based activities at health facilities, and individualized communications through household visits conducted prior to every IRS round as well as prior to each of the two LLIN mass distribution campaigns. Malaria prevention in pregnancy was promoted among pregnant women attending ante-natal clinics held at Government health facilities, where they were offered two doses of intermittent preventive therapy (IPTp; Fansidar™, IDA foundation, The Netherlands) from three months gestation one month apart. The initiative was evaluated by annual malaria indicator surveys (MIS) [11]. The results were complemented with data from the health information system (HIS) for 2009 and 2010 and entomological monitoring using light traps and human landing catches from 2007, 2009, 2010 and 2011 [12]. MIS were carried out at 17 sentinel sites between April and June of each year from 2007 to 2011. The sample size required for each MIS was determined based on an expected 30% reduction in malaria parasite prevalence among two to 14 year old children over the five-year initiative. Assuming a change in prevalence from 60% in year one to 42% in year five, with 80% power, 95% precision, a design effect of 1.5 between sentinel sites, and allowing for continuity correction, 191 children and 94 households were required per sentinel site. The sentinel sites were geographically spread throughout the four provinces so that there was at least one site per district. The exception was Bata district, the most populous, where there were five sites. Sentinel sites were: Akurenam, Bicurga and Niefang in Centro Sur province; Ebebeyin, Mico Miseng, and Nsok Nsomo in Kie-Ntem province; Ayamiken, Etofili, Kogo, Mbini, Ngolo, Ukomba and Yengue in Litoral province; Akonibe, Anisok, Mongomo, and Nsork in Wele-Nzas province (see map in [8]). Households were eligible for the survey if they included a pregnant woman or at least one child less than 15 years of age. Data were collected using Personal Digital Assistants (PDAs) in a survey programmed with Visual CE (SYWARE Inc., Cambridge, Massachusetts, USA) with data output to Microsoft Access® databases. Children under 15 years of age were tested for P. falciparum using RDT (ICT™ Malaria Combo Cassette ML02, R&R, Cape Town, South Africa) and had haemoglobin measured (HemoCue, Ängelholm, Sweeden), subject to parental consent. Anyone suspected of suffering from severe malaria was referred to and treated in hospital or clinic as appropriate according to national health guidelines. The national HIS was co-ordinated by the Ministry of Health and Social Welfare (MOHSW) of Equatorial Guinea with technical and financial support from MCDI. During the EGMCI, data were captured from approximately 90% of the Government’s health facilities located in the four continental provinces; 36 health centres, nine district hospitals and four regional and provincial hospitals. Private health facilities do not report health information to the MOHSW. HIS data were entered on patient registers (outpatient, inpatient, ante natal care) printed and distributed by the EGMCI and folio copies of pages were collected on a monthly basis and entered centrally by MOHSW staffs in a Microsoft Access database. Approximately 10% of known folio copies were not received at the MOHSW. Suspected malaria cases were recorded in the HIS based on clinician diagnoses entered in patient registers. Confirmed cases were those with either a positive RDT or blood slide. Entomological monitoring took place in all 17 sentinel sites. Mosquito specimens were initially collected on a monthly basis starting in December 2006 through August 2008 via a network of passive window traps installed in houses in each of the sentinel sites. Samples were sent to the Medical Research Council (MRC) South Africa for analysis. Collection volumes from these passive traps declined precipitously following the introduction of vector control activities, and ultimately were unable to produce sufficiently large quantities from which to reliably monitor infectivity levels. As such, starting in April 2009, trapping methods were changed and mosquito specimens were collected on a monthly basis, with the exception of September 2010 and Jan 2011, using light traps and human landing catches. Data collection ceased in June 2011. Specimens collected by light traps and human landing catches were sent to Yale University for analysis. Intact specimens captured using light traps and by human landing catch were analysed by PCR [13] and quantitative PCR (q-PCR) [14,15] to determine the presence of sporozoites and species identification [12]. In addition, gDNA aliquots extracted from window trap specimens (from January through September 2007) originally sent to MRC, were sent to Yale University for QPCR and PCR analysis. Bloodfed mosquitoes were excluded from testing for sporozoites to avoid specimens testing positive if they had ingested gametocytes. The sporozoite rate was calculated as the proportion of mosquitoes positive for sporozoites out of the total number tested. Children under one were excluded from tabulations and analysis a priori as maternal antibodies offer some protection from malaria. Measures of intervention coverage and malaria transmission for children aged 1–4 are reported as many organizations including UNICEF focus on children under five [16]. Prevalence for children aged 2–14 is also reported because sample size calculations were based on this age range. Indicators which were derived from the MIS include, (1) LLIN use, (2) proportion of households where IRS was reported in the previous six months, (3) proportion of under 5 febrile cases receiving ACT, (4) proportion of women pregnant within the last year who received at least two doses of IPTp, (5) prevalence of infection with P. falciparum, (6) prevalence of moderate to severe anaemia (haemoglobin<8g/dL), (7) prevalence of reported fever (temperature≥37.5°C)) in the two weeks prior to the survey. Analysis was carried out using Stata 12.1 software [17]. For the MIS, standard errors were adjusted to account for the survey design using the svy (survey) commands [18], where the primary sampling unit (PSU) was the sentinel site when reporting estimates combined over provinces and the household when reporting site level estimates. The effect of LLINs and IRS (living in a site targeted for these interventions or actually receiving them) on P. falciparum prevalence in children 1–4 years was determined by logistic regression, adjusting for survey year, household size and markers of socioeconomic status as individual covariates (access to a flush toilet, water source, light source, type of cooking fuel). Of these confounders, any for which the confidence interval included the null in the adjusted model, and which when removed did not change the main Odds Ratio (OR), were removed for the sake of parsimony. There were two kinds of missing data; data where status was reported unknown (in the case of IRS and LLIN use) and data where results were unavailable (in the case of a child not being present for an RDT or haemoglobin test). This study was approved by the ethics committees of the Ministry of Health and Social Welfare of Equatorial Guinea and the London School of Hygiene and Tropical Medicine. Written informed consent was obtained from all parents or caregivers of the children who participated in the MIS. Anyone testing positive by RDT in the MIS was referred to a local clinic for appropriate treatment according to national policy.

Based on the information provided, here are some potential innovations that could be used to improve access to maternal health in Equatorial Guinea:

1. Mobile Health (mHealth) Solutions: Implementing mobile health technologies, such as SMS reminders for prenatal care appointments and health education messages, can help improve access to maternal health information and services.

2. Telemedicine: Introducing telemedicine services can allow pregnant women in remote areas to consult with healthcare professionals and receive prenatal care without having to travel long distances.

3. Community Health Workers: Training and deploying community health workers can help bridge the gap between healthcare facilities and pregnant women in underserved areas. These workers can provide basic prenatal care, health education, and referrals to healthcare facilities when necessary.

4. Maternal Health Vouchers: Introducing a voucher system for maternal health services can help reduce financial barriers and improve access to quality prenatal care, delivery, and postnatal care.

5. Transportation Solutions: Improving transportation infrastructure and implementing transportation schemes specifically for pregnant women can help overcome geographical barriers and ensure timely access to healthcare facilities.

6. Maternity Waiting Homes: Establishing maternity waiting homes near healthcare facilities can provide a safe and comfortable place for pregnant women to stay during the final weeks of pregnancy, ensuring they are close to medical care when they go into labor.

7. Maternal Health Education Programs: Implementing comprehensive maternal health education programs can empower pregnant women with knowledge about prenatal care, nutrition, and birth preparedness, leading to improved health outcomes.

8. Strengthening Health Information Systems: Enhancing health information systems can help collect and analyze data on maternal health indicators, enabling policymakers to make informed decisions and allocate resources effectively.

9. Public-Private Partnerships: Collaborating with private sector organizations can help leverage their resources and expertise to improve access to maternal health services, such as through the provision of mobile clinics or funding for infrastructure development.

10. Quality Improvement Initiatives: Implementing quality improvement initiatives in healthcare facilities can enhance the overall quality of maternal health services, ensuring that pregnant women receive safe and effective care.

It is important to note that the specific context and needs of Equatorial Guinea should be taken into consideration when implementing these innovations.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health in Equatorial Guinea is to focus on scaling up coverage of both long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) interventions. The study showed that children aged 1-4 who used an LLIN the previous night or lived in a sprayed house had lower prevalence of Plasmodium falciparum infection compared to children with neither intervention. Additionally, children who benefited from both LLINs and IRS had the lowest prevalence of infection.

To implement this recommendation, the following steps can be taken:

1. Increase the distribution of LLINs: Ensure that pregnant women attending antenatal clinics receive LLINs, as this has been shown to be effective in reducing malaria prevalence. Collaborate with healthcare facilities to provide LLINs to pregnant women during their visits.

2. Expand indoor residual spraying: Increase the coverage of IRS in provinces where it has been shown to be effective. This can be done by allocating more resources and funding to carry out regular and comprehensive IRS campaigns.

3. Improve communication and education: Implement a comprehensive information, education, and communication (IEC) strategy to raise awareness about the importance of LLINs and IRS in preventing malaria. This can include mass media campaigns, group-based activities at health facilities, and individualized communications through household visits.

4. Strengthen monitoring and evaluation: Establish a robust monitoring and evaluation system to track the coverage and impact of LLINs and IRS interventions. This will help identify areas that need further improvement and ensure that interventions are reaching the target population effectively.

By implementing these recommendations, it is expected that access to maternal health will be improved by reducing the prevalence of malaria in pregnant women and their children. This will contribute to better maternal and child health outcomes in Equatorial Guinea.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health in Equatorial Guinea:

1. Increase the distribution and use of long-lasting insecticidal nets (LLINs) among pregnant women: LLINs have been shown to provide individual protection against malaria. By ensuring that pregnant women have access to LLINs and are educated on their proper use, the risk of malaria infection during pregnancy can be reduced, leading to improved maternal health outcomes.

2. Strengthen the implementation of indoor residual spraying (IRS): IRS has also been proven to be effective in reducing malaria transmission. By expanding the coverage and frequency of IRS in areas with high malaria prevalence, the risk of infection can be further reduced, benefiting pregnant women and their unborn children.

3. Improve case management for pregnant women with malaria: Ensuring that pregnant women receive prompt and appropriate treatment for malaria is crucial for their health and the health of their babies. This can be achieved by training healthcare providers on the diagnosis and treatment of malaria in pregnancy and ensuring the availability of effective antimalarial medications.

4. Enhance information, education, and communication (IEC) campaigns: Comprehensive IEC campaigns can play a vital role in improving access to maternal health services. These campaigns should focus on raising awareness about the importance of antenatal care, malaria prevention, and the availability of services for pregnant women.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Collect baseline data: Gather information on the current coverage and utilization of maternal health services, including antenatal care attendance, LLIN and IRS coverage, and malaria prevalence among pregnant women.

2. Define indicators: Identify key indicators to measure the impact of the recommendations, such as the proportion of pregnant women using LLINs, the proportion of pregnant women receiving IRS, and the prevalence of malaria among pregnant women.

3. Develop a simulation model: Create a mathematical model that simulates the impact of the recommendations on the selected indicators. The model should take into account factors such as population size, geographical distribution, and the effectiveness of the interventions.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to estimate the potential impact of the recommendations over a specified time period. The simulations should consider different scenarios, such as varying levels of LLIN and IRS coverage.

5. Analyze results: Analyze the simulation results to determine the potential impact of the recommendations on improving access to maternal health. Assess the changes in the selected indicators and compare them to the baseline data.

6. Validate and refine the model: Validate the simulation model by comparing the simulated results with real-world data, if available. Refine the model based on feedback and additional data to improve its accuracy and reliability.

7. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community members. Use the results to advocate for the implementation of the recommended interventions and to guide decision-making processes.

By using this methodology, policymakers and stakeholders can gain insights into the potential impact of the recommendations on improving access to maternal health and make informed decisions on resource allocation and program implementation.

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