A prospective cohort study to assess the micro-epidemiology of Plasmodium falciparum clinical malaria in Ilha Josina Machel (Manhiça, Mozambique)

As part of the Millennium Development Goals (MDGs) established by the United Nations in the year 2000, all malaria-endemic countries concentrated their efforts on reducing malaria incidence globally by 2015. In the last decade, 55 of the 106 countries with ongoing malaria transmission reached the target set in Objective 6 to reduce their malaria burden by 75 %. However, these countries contributed only to 6 % of the global estimated cases, suggesting that countries with the most affected populations, most of them from sub-Saharan Africa, have yet to reach this target [1].

Mozambique is part of the ten countries with the highest malaria endemicity in the world. Transmission intensity varies widely within the country, with high transmission intensity occurring in the north and a decreasing pattern observed as provinces are closer to the south of the country [2‐4]. However, high transmission hotspots can still be found within wider low transmission areas. Despite the increasing funding available for malaria control, Mozambique has experienced an increase in malaria incidence since 2007, according to national malaria surveillance data [1]. Although it is not clear what the main factors are driving these increasing malaria incidence trends, coverage of malaria control interventions is heterogeneous, and interventions are not delivered on a regular basis [2, 5]. Indoor residual spraying (IRS) was first introduced in urban areas in 1994, whereby only ten districts in the country were selected. Insecticide-treated nets (ITN) deployment only started in 2004, primarily through donor funding. The south of Mozambique also took part in the Lubombo Spatial Development Initiative (LSDI), a tri-lateral initiative between the governments of Swaziland, South Africa and Mozambique that took place in the early 2000s, and officially finished its activities in 2011 [6, 7].

Monitoring malaria trends in the different areas of the country and characterizing changes in clinical presentation and age distribution of malaria cases during shifts in transmission is crucial to inform policy. High-quality, health facility-based surveillance data, despite the potential selection bias due to differences in health-seeking behaviour and accessibility, allow finely characterizing of clinical malaria epidemiology of an area over time, offering accurate and detailed information that can complement information on trends observed through the national health management information system. Data from the Manhiça Health Research Centre (CISM) outpatient paediatric morbidity surveillance system, operating in the southernmost province of Mozambique, identified heterogeneous epidemiological patterns within its study area. This study aims to analyse the epidemiological trends of the outpatient clinical malaria cases from 2003 until 2013 in an area of high endemicity within the district if Manhiça, that experienced a drop in transmission after IRS, ITNs, and artemisinin combination therapy (ACT), followed by a later resurgence of clinical cases. Evidence from this analysis may offer the National Malaria Control Programme (NMCP) additional insight on the clinical malaria profile that could be observed in other areas of the country that have experienced similar changes in malaria transmission.

A total of 70,698 visits were conducted at the outpatient clinic of the IJMHP between 1 July 2003 and 30 June 2013. The number of annual visits steadily increased over the years, ranging from 5735 visits in 2003–2004 to 9851 visits in 2012–2013 (Table 1). The mean age of all paediatric visits steadily increased from 3.4 to 5 years during the study period. Females represented 51 % of the outpatient visits, and 36 % of the cases presented with fever at time of visit every year. Malaria testing rates were constantly above 95 % for any case with fever or who reported to have fever in the previous 24 h.

More than half of all outpatient visits to the IJMHP between 2003 and 2006 were due to clinical malaria (51 % in the season of 2003–2004, 61 % in 2004–2005, and 57 % in 2005–2006). A sharp decline was observed between 2007 and 2009, when less than a quarter (23 %) of all visits to the health facility were associated with malaria. From 2009 onwards, the number of clinical malaria cases increased steadily reaching again 51 % of all outpatient visits in 2012–2013. A similar trend was observed when analysing slide positivity rates (SPRs) (Fig. 3).

The mean age of clinical malaria cases presenting to the IJMHP steadily increased for every seasonal year, shifting from 2.9 (SD 2.8) years in 2003–2004 to 5.7 (SD 3.5) year in 2012–2013. A different trend in mean age was observed among non-malaria cases, which was 3.9 (SD 3.8) in 2003–21004 and decreased to a minimum of 3.2 (SD 3.6) in 2006–2007, and increased steadily until 2012–2013, when it was 4.4 (SD 3.9) (Fig. 4a). The DID analysis to compare age shifting patterns between malaria cases and non-cases showed a significantly larger increase in the mean age of patients with malaria than those with other pathologies. In general, the increase in malaria case ages was significantly higher for every year compared to the previous one except for 2007–2008 compared to 2006–2007 and in between 2009 and 2012, where the increase in age was similar in both groups (Fig. 4b).

Out of all clinical malaria cases attending the IJMHP between 2003 and 2013, 46.8 % were mildly anaemic, 13.4 % moderately anaemic and 0.7 % suffered from severe anaemia. A significant increase in the mean PCV among clinical malaria cases was observed, shifting from 29.7 % (95 % CI 29.4–29.8) in 2003–2004, to 32.4 % (95 % CI 32.2–32.5, p < 0.0001) in 2012–2013. Figure 5a presents the changes in PCV levels by age group throughout the study period. Infants had a lower PCV compared to 1–4 and 5–14 year olds during the entire study period, with an increasing trend observed from 2003–2004 (mean PCV 26.9 %, 95 % CI 26.5–27.4) to 2012–2013 (mean PCV 30.2 %, 95 % CI 29.3–31.0).

GMPs among clinical malaria cases experienced a steady and significant increase from 5778 parasites/µL in 2002–2003 to 17,316 parasites/µL in 2012–2013 (p < 0.0001). Stratification by age group revealed that the overall shift in GMP was mainly driven by children older than 1 year who experienced infections of significantly higher GMPs every year, with the steepest increase in children of 5–14 years old. On the other hand, GMPs of infants were similar over time, with a minor drop in 2008–2009 (Fig. 5b).

The clinical malaria MCBIRs at the IJMHP experienced a similar pattern to that observed for the proportion of total visits with clinical malaria, starting with 667 cases per 1000 CYAR (95 % CI 639–697) in 2003–2004, and decreasing to 206 cases per 1000 CYAR (95 % CI 191–221) in 2007–2008. A resurgence was later observed, reaching a total of 871 cases per 1000 CYAR (95 % CI 840–903) in 2012–2013, the zenith of the documented incidence in the area. Table 2 presents the clinical malaria MCBIRs and IRRs for every year of the study overall and by age group. Overall, children aged 1–4 years experienced the highest number of incident clinical cases per 1000 CYAR at any point in time except for the first year, and children aged 5–14 years were the age group with the lowest incidence during the majority of the study period.

Clinical malaria MCBIR trends varied significantly between different age groups throughout the study period. Incidence rates among infants consistently decreased to a third of the baseline levels by 2012–2013 (RR = 0.3, 95 % CI 0.3–0.4, p < 0.001). One to 4 years olds also experienced a 70 % reduction in the rate of clinical malaria cases between 2003–2004 and 2007–2008 (RR = 0.3, 95 % CI 0.3–0.3), although this was not maintained, and an increasing trend was later observed, reaching similar incidence levels to those of 2003–2004 in 2012–2013 (RR = 1.0, 95 % CI 0.9–1.0). Finally, clinical malaria cases per 1000 CYAR among children older than 5 years remained unchanged between 2002 and 2009, and experienced a significant increase until 2013. By the last year of the study period, the incidence among children older than 5 years was 3.8 (95 % CI 3.4–4.3) times higher than it was in 2003–2004 (Fig. 6).

This study aimed to characterize the epidemiological trends of clinical malaria observed over a period of 10 years at a rural health centre in an area that had a high malaria transmission in 2002 and experienced a drop in malaria cases followed by a subsequent resurgence. IJMHP experienced a drop in clinical malaria cases between 2004–2005 and 2007–2008 followed by a resurgence of cases observed until the end of the study period in 2012–2013, detecting similar clinical malaria positive rates in 2012–2013 as that observed in 2003–2004. These patterns resemble those observed in the rest of Mozambique, that despite increasing availability of funding for malaria control, has experienced an increase in the number of malaria cases reported to the NMCP since 2009 after a previous drop of cases [1]. Nevertheless, the national health management information system does not yet offer complete and accurate data that allows further characterization of the profile of malaria cases observed nationally, and data from Malaria Indicator Surveys are outdated (last performed in 2007).

In Ilha Josina Machel, a sharper increase of clinical cases was observed particularly among children on their first to fifth birthday between 2007 and 2013, as well as those between the ages of 5 and 15 years. Overall, a shift in the age distribution of the clinical malaria cases towards older children was observed particularly among malaria cases, indicative of an alteration in the transmission intensity patterns in the area [13] and a potential consequent impact on the naturally acquired immunity (NAI) of the population.

The current analysis does not allow for any assessment of causality to evaluate which factors contributed to the decline and subsequent rise in transmission in the area. Rainfall patterns during the study period show a decrease in precipitation levels around the same years as malaria cases started to drop. This suggests that environmental factors may have had a considerable effect on the epidemiology of malaria in the past decades. Further spatiotemporal studies in the area shall be conducted to more accurately measure the impact of climatic factors on malaria through time. However, it is plausible that the introduction of new malaria control measures also played an important role in the initial decline in transmission. IRS was first deployed in Ilha Josina Machel in 2004–2005, according to district records, which correlates with the observed decrease in incidence between 2006 and 2009. However, an increase in the number of clinical malaria cases was later observed, which could be associated with a decrease in the IRS effectiveness due to low coverage (as reported between 2010 and 2013), or lack of continuity of IRS activities (such as in 2011). In fact, malaria resurgences have been observed in a number of different settings across the world since the beginning of the twentieth century, most of which are attributed to weakening of malaria control programmes due to resource constraints, and a subsequent inability to ensure continuity of IRS in places where it had already been delivered [14].

The sudden drop in the number of clinical malaria cases between 2007 and 2009 possibly correlates with a consequent drop in transmission intensity of malaria in the area at that time, considering that no changes were made in the reporting system and that malaria-testing rates remained constant throughout this period. The significant shift in the age distribution of clinical malaria cases towards older children observed in IJMHP supports this hypothesis, as in lower transmission settings young children will be exposed to less infectious bites and will take longer to build up a naturally acquired immunity, with older children having a relatively high incidence of clinical malaria [15, 16]. Unpublished entomological data from Ilha Josina of 2006 and 2007 further support this drop in transmission, showing an entomological inoculation rate (EIR) of 77 infectious bites per person during the dry season of 2006, to an EIR of 0.8 during the dry season of 2007. Similar shifts in the age distribution of clinical malaria cases as a function of transmission intensity have been extensively reported in the past in other sub-Saharan African countries [17‐21].

The low-transmission period between 2007 and 2009 was followed by an immediate increase in the incidence of clinical malaria cases, particularly among 1–4 years olds and later also in the 5–14 years olds. During the lower malaria transmission period there was a decrease in the exposure to parasites in children (evident in the incidence rates among infants since 2007), delaying the acquisition of NAI in younger children and diminishing the premunition in older children that had already developed some NAI during the previous years [22]. Several studies, conducted to evaluate this question through actively interrupting exposure to the parasite using chemoprophylaxis at a very young age, have reported a similar rebound effect in the incidence of clinical malaria cases among children in the treatment arm, up to 1 years after treatment [15, 23‐25]. The biological mechanisms driving the acquisition of NAI are still not well understood; however, evidence from mathematical models [26, 27] and immunological studies [28, 29] clearly identify age, exposure to the parasite and transmission intensity as important factors involved in this process.

The lower increase in the incidence rate of clinical malaria cases among infants may be partly explained by a drop in transmission; however other interventions such as the introduction of vector control activities targeting pregnant women and infants could have also contributed to an increased protection against parasite exposure among this age group.

The age-specific GMP trends observed in this study, with significant increases in parasitaemia in children older than 1 year after 2007 also show a slower acquisition of NAI with age and a lower ‘anti-parasite’ immunity [22]. In addition, the increase of mean PCV with age despite a raise in parasitaemia could possibly be a reflection of lower chronic infections or lower number of episodes per year, which cause less anaemia and does not allow the anti-parasite immunity to develop fast, resulting in the delay in the rate of NAI and the observed high parasitaemic infections.

Insecticide resistance may also be a contributing factor to the observed resurgence in the number of clinical malaria cases in the area. Mosquito resistance to pyrethroids was first reported in 2011 in a nearby sugar cane plantation of Maragra in the district of Manhiça [30]. Another study in a Northern province also reported wide resistance to pyrethroids and carbamates in 2007 [31]. Entomological data from CISM further supports these findings revealing less than 9.6 % sensitivity to pyrethroids among the A. funestus population of the district of Manhiça [32]. Insecticide resistance to pyrethroids has serious implications regarding the likely impact of LLINs towards reducing malaria transmission in the area, which since 2011 may have contributed to the increasing malaria incidence trends in the area.

The estimates obtained from this analysis are subject to a series of limitations. First, access to health care may have increased through the years. This could have caused an underestimation of the malaria burden in the area on the first years of the study, and a consequent overestimation of IRRs when comparing rates across years. Second, IJMHP data are also susceptible to the Hawthorne effect [16], as the presence of CISM, its impact on case management as well as research studies conducted, may affect the overall epidemiology of malaria in the study area of Manhiça. Particularly, Ilha Josina Machel was included as one of the sites where the RTS,S vaccine trials took place between 2002 and 2008. This analysis was also affected by missing data of PCV particularly in the last years of the study, which may have affected the estimates of severe and mild anaemia cases during these years.

Additionally, this study aims to provide a temporal description of the clinical malaria epidemiology in a health facility. Therefore, it did not conduct any sociodemographic or environmental risk factor analysis, which would enrich the interpretations withdrawn from the results obtained from this particular assessment. Separate studies should be conducted to respond to the hypothesis raised in this study, identify the main drivers of malaria transmission in the area and determine the social factors that may put a resident in the area at a higher risk of malaria than others.

This study shows a reduction in the clinical malaria incidence in a small area of initially high transmission in Southern Mozambique, and a subsequent resurgence of cases. Evidence from this study indicates that efforts to control malaria and reduce transmission need to be sustained over time in order to guarantee gains in the long term. Malaria control programmes with limited resources, such as the one in Mozambique, should consider malaria control interventions that ensure sustainability and target the most vulnerable populations, particularly infants and children under 5, at all times. Considering the costs and operational difficulty of this task, NMCPs should consider investing in innovative strategies to drastically interrupt transmission and eliminate the parasite reservoir from communities in a short period of time, and subsequently concentrate efforts to manage and eliminate remaining foci of transmission and imported infections.