Malaria morbidity and mortality in Ghana have been largely declining [6, . This decline has also been found in malaria in pregnancy; a condition which has direct effects of clinical malaria in pregnancy and congenital malaria (using neonatal malaria as a proxy in this article). However, authors of this study doubted that the decrease in malaria in pregnancy was not equitable across the country. Consequently, this study sought to establish the existence of hotspots of malaria in pregnancy (if any) in Ghana. These hotspots were measured using incidences of clinical malaria in pregnancy and neonatal malaria.
Clinical Malaria in Pregnancy
The average proportion of clinical malaria in pregnancy was 347.60 per 1000 women. The proportion was highest in 2016 compared to 2014 and 2015. The high incidence for the 2016 year may be attributed to better reporting and not an increase in incidence. Indeed, the introduction of routine data reporting on the platform DHIMS2 has improved to a large extent the quality of data collated from health facilities. Therefore, an increase in proportion of clinical malaria in pregnancy could be linked more to improved reporting. Correspondingly, the assertion of better reporting has also been made by Rouamba, Samadoulougou, Tinto, Alegana and Kirakoya- Samadoulougou (16). Notwithstanding the assertions of improved reporting, Rouamba et al(16) indicated that the World Health Organisation (WHO) has reported increases in global cases of malaria.
Also consistent with the argument of better reporting is the consistent reduction in the prevalence of malaria since the revamping of malaria intervention in 2004. For example, malaria prevalence reduced between 2011 and 2016; from 27.5 % in 2011 (MICS, 2011) to 26.7% in 2014 (GDHS, 2014) to 20.4% in 2016 (Malaria Indicator Survey, 2016) (5) (NB: These figures are from different data sources, but the tools and the respective questions are similar. Therefore inferences can be drawn (5)). From the foregoing possible attributions, further research is needed to ascertain the cause of the increase in burden in 2016.
Figure 1 shows maps of uncomplicated between 2014–2016, and Ghana was found to have an average of zero z-score for clinical malaria in pregnancy. This generally indicates that interventions for fighting malaria (including those targeted for clinical malaria in pregnancy) were largely effective. The average zero z-score for these three years is consistent with findings from Aregawi et al (15). That is, Aregawi et al (15) identified that among all ages, outpatient malaria cases dropped by 57% (95% CI, 47–66%) by first half of 2015.
Nevertheless, hotspots were identified in the country. Some hotspots were stable while others showed variation both geospatially and chronologically year on year. This finding contrasts the results of Bousema at al (12) who identified stable hotspots in his study.
Stable hotspots were identified in the southern part of Western Region for the three years. They include Prestea Huni Valley, Tarkwa Nsuem, Wassa East and Mporhor. Findings of stable hotspot are consistent with those documented by Bousema and others (12) and Kamuliwo et al (9) for clinical malaria in pregnancy. Kamuliwo et al (9) also found stable hotspots (z-score > 2.58) in the north-eastern and south-eastern parts of Zambia.
Another point of interest is that, the districts in which these hotspots were found are largely rural. This finding is consistent with literature, in which greater levels of malaria transmission are found in rural areas compared to urban areas. For example, a desk review, triangulated data from entomological studies and the 2011 Malaria Indicator Cluster Survey (MICS) in the 2012 Ghana Malaria Urban Study (17). The study confirmed higher malaria transmission in rural areas. Stable hotspots in these rural areas may be due to poor health seeking behaviour because of barriers with respect to geographical access. Such an assertion has also been made by Wiru, Oppong, Gyaase, Agyei, Abubakari, Amenga-Etego, Zandoh & Asante(18). Wiru et al(18) attributed malaria mortality hotspots in their study to districts being mostly rural.
A second reason for these stable hotspots was that they were found mostly in the Forest Ecological Zone. These districts have had their environment largely degraded by illegal mining, resulting in large pools of water suitable for the breeding of the anopheles mosquito (19). The proliferation of such collections of water is likely to lead to an increased number of mosquitoes. Therefore, this increase in mosquitoes, would result in elevated entomological inoculation rates and its related upsurge in malaria transmission rates (20).
In spite of the stability in some hotspots, there were also variability in other hotspots for clinical malaria in pregnancy. In Western Region for example, hotspots reduced from 15 in 2014 to 7 in 2016. This finding is consistent with the reduction of parasite prevalence of malaria (among children less than 5 years) in country-wide surveys of 2014 MICS and 2016 MIS. These two surveys also showed a reduction of parasite prevalence from 39% (2014 MICS) to 22% (2016 MIS)(21). It would imply that malaria transmission has reduced significantly within the two years.
In fact, variability in hotspots in those areas may also be attributed to the level efficiency of the health system; using its six building blocks (i.e. leadership/governance, healthcare financing, health work force, service delivery, health information system and medical products and technologies(22)). Of particular relevance to this study is the improved availability of malaria logistics (in this case, the availability and use of ITNs and sulphadoxine-pyrimethamine (SP) for intermittent preventive treatment (IPTp)). Unfortunately, factors such as supply chain blockages have been found to be a challenge. For example, availability of SP varies year-on-year depending on whether there is accessibility, shortages or mal-distribution at the facility level (23). For instance, in 2016 there were stock outs of SP at the facility level but there were stocks at the regional level (6). Indeed, Bhushan and Bhardwaj (24) identified that some health system effects such as quality of care and critical shortages in commodities had impact on transmission, further impeding reduction in maternal and newborn mortality.
Lastly, variability in hotspots may also be linked to pathogen’s natural history (20). For instance, Paull et al (20) identified geospatial heterogeneity as being responsible for transmission of diseases such as SARS and Typhoid. They however concluded that such variability was caused by host factors in 20% of the cases and transmission events in 80% of cases.
Studies on neonatal malaria are scarce because neonatal malaria is not thought to be common. Therefore, studies to identify hotspots of neonatal malaria are not common either. Albeit, Makhtar (25) in his review of literature reported that neonatal malaria is not as rare as was originally anticipated. Indeed, a meta-analysis by Park, Nixon, Miller, Choi, Kurtis, Friedman & Michelow found a significant pooled adjusted hazard ratio of 1.46 (95% CI, 1.07–2.00; P < .001) for neonatal malaria (26). Additionally, by extrapolation, a congenital malaria was initially misdiagnosed because Kane, Diallo, Dembélé, Fané, et al, (27), did not initially test for neonatal malaria.
Hence, it was not surprising that the review of neonatal malaria incidence for the years 2014–2016 from routine data showed that neonatal malaria in Ghana existed. The review further showed that there were less male neonatal malaria cases reported than females (1:1.15) (Table 2). Lower proportion of males than females with neonatal malaria contradicts findings by Runsewe-Abiodun et al in Nigeria; who found more males than females (1.6:1) had neonatal malaria (28). Runsewe-Abiodun et al’s study however reported that the infection was not sex-linked and hence the difference in sex distribution in the two studies cannot be linked to the disease (28).
Our study also revealed that Ghana largely had a zero z-score for neonatal malaria; although hotspots were identified in all the three years under review. Nevertheless, these hotspots for neonatal malaria showed variability year-on-year as with those found for clinical malaria in pregnancy. Hotspots for neonatal malaria were found in the forest ecological zone and rural areas. Hotspots in these identified areas are in tandem with literature because forest zones and rural areas have been documented to have high transmission rates (17).
These hotspots even increased in number in 2016. The increase in hotspots may also be due to better reporting as has been stated above. The increase in hotspots may also be attributed to increased resistance of malaria parasites to the prevailing antimalarial drugs and increased virulence (29).
In spite of hotspot variability, some districts were consistent with hotspots for neonatal malaria for 2015 and 2016 in Ashanti and Brong Ahafo Regions. In addition, it is noted that there was a persistent hotspot in Bole in the western border of Northern Region for two consecutive years (2014–2015). Since Bole is in the western border with la Côte d’Ivoire, it could be that there was consistent transmission across borders.
In 2016, some parts of Northern Ghana (Kumbungu, Tolon and Wa West) had hotspots for neonatal malaria. Some of these districts had the intervention of Indoor Residual Spraying (IRS) discontinued. The emergence of these hotspots may thus be due to suspension of IRS; leading to a rebound effect of malaria cases; particularly for the neonates. This is of particular importance because malaria transmission in Northern Ghana tends to be more seasonal and therefore children in these part are more vulnerable.
Notwithstanding, Kumbungu continues to receive IRS and therefore hotspot can not be completely attributed to a rebound malaria incidence. Additionally, the attribution may not necessarily be associated with cessation of IRS because findings from Kamuliwo et al’s work (9), showed the protective effect of IRS.
One must note, albeit, that the neonatal hotspots are few and therefore largely IRS has had protective effect in other districts particularly because there is significant reduction in prevalence of malaria in the three regions in the north (5). It will be informative to undertake further studies to ascertain the persistent case of hotspots in Northern Ghana.
Interaction of Clinical Malaria in Pregnancy and Neonatal Malaria Hotspots
Generally, districts with hotspots for clinical malaria in pregnancy and neonatal malaria respectively were not the same. This buttresses the findings of Menendez and Mayor (30) that neonatal malaria may have been and identified within the first few days of life.
Yet, of significant interest is that of Bole District, which was found to have elevated levels of both clinical malaria in pregnancy and neonatal malaria for the year 2015. It is therefore supposed that a significant proportion of the clinical malaria may have been vertically transmitted from mothers to the neonates; giving incidences of congenital malaria. This would be recorded as neonatal malaria because the DHIMS 2 data collection platform does not segregate data into first 7 days and above. This assertion is supported by the meta-analysis by Park et al (26). Indeed, Nhama, Varo and Bassat (31) in their commentary have called for further investigation into incidences of suspected congenital and neonatal malaria cases as their burden may be more than may have been originally thought of. Further investigation into effects of stillbirths, congenital anaemia from the neonate in relation to the women with clinical malaria in pregnancy is needed to confirm if reported neonatal malaria in Bole can be attributed to congenital malaria.